Radomir, Rocío, Xavier, Mariangela, Núria, Hervé Alvaro

Ali Marc

Pe- ter, David Dan Guillaume

Ariel Giorgos

L Baudis

M Bomben

G Mar

L Scotto

Lavina To

Raquel Simone

Michelangelo Traina: Search for Light Dark Matter and Exploration of the Hidden Sector with the

Then as it was, then again it will be And though the course may change sometimes Rivers always reach the sea Blind stars of fortune, each have several rays On the wings of maybe, downing birds of prey Kind of makes me feel sometimes, didn't have to grow But as the eagle leaves the nest, it's got so far to go.

Ainsi, la matière noire devrait représenter plus de 80% de la masse de l'Univers.

Un vaste bestiaire de particules candidates a été théorisé, le paradigme des particules massives à interaction faible (WIMP) dominant le paysage. Les efforts expérimentaux des dernières décennies n'ont pas réussi à détecter les WIMP pour des masses entre 10 et 10 4 GeV/c 2 , motivant ainsi la recherche de matière noire plus légère. Les expériences DAMIC (DArk Matter In CCDs) visent à la détection directe de WIMP légers et de candidats du secteur caché au moyen de dispositifs à transfert de charges (CCD) en silicium épais.

Le détecteur DAMIC de SNOLAB (∼40 g) se trouve sous un mort-terrain rocheux de 2070 m dans la mine de Vale Creighton au Canada. Ses CCD se caractérisent par un bruit de lecture de l'ordre d'un électron, un courant de fuite minimal (∼10 -4 e -/pixel/jour) et une excellente résolution spatiale (∼15 µm). Le détecteur DAMIC-M, avec une masse de l'ordre de 1 kg, sera hébergé au Laboratoire Souterrain de Modane (LSM), à 1700 m sous le pic du Fréjus, en France. Ses capteurs CCD comportent des amplificateurs skipper, qui permettent une résolution d'une fraction d'électron en réalisant mesures non destructives des charges. L'objectif de minimisation du bruit de fond de DAMIC-M est de 0, 1 dru (0, 1 événement par keV-kg-jour), une amélioration de deux ordres de grandeur par rapport à l'installation de SNOLAB.

Ce travail de thèse s'articule autour de deux grands thèmes : la construction du premier modèle de bruit de fond CCD complet dans le cadre de DAMIC à SNOLAB, et les efforts de recherche et développement vers les objectifs scientifiques de DAMIC-M, notamment avec le déploiement de son détecteur prototype, la Low Background Chamber (LBC).

Le modèle de bruit de fond de DAMIC à SNOLAB est construit à partir xiii Despite a conspicuous, statistically-significant excess of events below 200 eV, this analysis places the strongest exclusion limit on the WIMP-nucleon spinindependent scattering cross section with a silicon target detector for masses < 9 GeV/c 2 . DAMIC-M is set to achieve a few technological milestones on the way to its science goals. The deployment of skipper CCDs with custom electronics will lower detection thresholds down to ∼10 eV, simultaneously enabling higherprecision detector characterization. Cryogenic test chambers are set up across institutions to conduct systematic CCD testing and design a selection process in view of DAMIC-M CCD production. A protocol is defined to establish detector grade and characterize detector performance. The test chamber constructed at LPNHE is additionally used to commission instrumentation for the LBC prototype experiment at LSM. The Low Background Chamber is commissioned for operations in late 2021. High electronic noise (∼10 e -) and leakage current (∼10 In the present chapter, the main evidence for dark matter is discussed, in particular focusing on its particle nature. Theories of modified gravity and macroscopic astrophysical candidates are only touched upon, for sake of completeness. Particle dark matter detection strategies are finally summarized to lay the foundations for the following chapters, which delve into the DAMIC direct detection experiments.

evidence in astrophysics and cosmology

The first milestone for modern Dark Matter research is F. Zwicky's work from the first half of the XX century. Zwicky estimated the velocity dispersion of galaxies belonging to the Coma cluster based on the virial theorem, alongside with its mass and size. The result of this calculation, 80 km/s, turned out inconsistent with the observed average velocity dispersion: ∼1000 km/s. He commented that [START_REF] Zwicky | Die Rotverschieb ung von extragalaktischen Nebeln[END_REF]: "If this would be confirmed, we would get the surprising result that dark matter is present in much greater amount than luminous matter". A few years later, in 1937, Zwicky published refined calculations on the Coma cluster, this time showing that the observed velocity dispersion led to a very large mass-to-light ratio of about 500M /L (solar units). Although his estimate was off by a factor ∼2, the conclusion would not have changed:

there must be an invisible source of gravity affecting the dynamics of the cluster. For Zwicky, however, this was likely cold stars and ordinary matter in all physical states [START_REF] Zwicky | On the Masses of Nebulae and of Clusters of Nebulae[END_REF]. A space-telescope image of the Coma cluster is shown in Figure 1.1. Similar results were also reported by S. Smith concerning the mass of the Virgo cluster, analyzing the radial velocities of its members. According to his calculations, the cluster mass was ∼200 times larger than Hubble had estimated relying on the spectrographic rotation method [START_REF] Hubble | The Realm of the Nebulae. Mrs. Hepsa Ely Silliman[END_REF]. Smith acknowledged some form of low luminosity inter-nebular material as the cause of such discrepancy, while Hubble considered the discrepancy "real and important" [START_REF] Hubble | The Realm of the Nebulae. Mrs. Hepsa Ely Silliman[END_REF].

The astronomical community remained dubious for a while faced with these results and by the 1950's several alternative explanations had been formulated. At first, it seemed unlikely that some of the faster galaxies observed could effectively be part of the clusters. They might be temporary hyperbolicorbit by-passers. However, excluding outliers from calculations invariably resulted in high dispersion velocity and anomalous mass-to-light ratios [START_REF] Schwarzschild | Mass distribution and mass-luminosity ratio in galaxies[END_REF]. The applicability of the Virial theorem was questioned too. In particular, the hypothesis of dynamic stability was put under scrutiny. It was nonetheless concluded that Coma could at most be at the very beginning of a slow expansion state [START_REF] Burbidge | The Hercules Clusters of Nebulae[END_REF], thus maintaining the applicability of the theorem. By the 1960's the consensus was that more data was needed to understand these discrepancies.

Astronomers started speculating about the nature of the elusive dark mass and its distribution in the clusters. Gas was the first state of matter to be ruled out as the inter-galactic source of gravitational pull thanks to researches by A. Penzias and others [START_REF] Penzias | Free Hydrogen in the Pegasus I Cluster of Galaxies[END_REF][START_REF] Meekins | Physical Sciences: X-rays from the Coma Cluster of Galaxies[END_REF]. Later, massive astronomical bodies like invisible collapsed objects and dwarf stars would also be excluded. The focus of the community would eventually shift towards non-baryonic matter [START_REF] Bertone | A History of Dark Matter[END_REF].

Galactic rotation curves

Galactic rotation curves are velocity profiles of the aggregate of physical bodies present in stellar-system size regions of space as a function of the galactocentric distance. The concept is meaningful for spiral galaxies, where a good aggregate estimate is possible due to the fact that stars are orbiting coherently with respect to the center of the galaxy. 1 Galactic rotation curves are the first compelling evidence for non-baryonic dark matter. It is once they come up that the possibility of invisible mass is taken seriously by the astronomical community. The first measurement of galactic rotation curve is from H.

Babcock [START_REF] Babcock | The rotation of the Andromeda Nebula[END_REF]. Despite measuring increasing velocities as a function of the galactocentric distance in Andromeda (or M31), Babcock dismissed the findings as instrumental artifacts. In the 1970's, higher precision measurements on galactic rotation curves by V. Rubin and others [START_REF] Vera | Rotation of the Andromeda Nebula from a Spectroscopic Survey of Emission Regions[END_REF][START_REF] Rogstad | Gross Properties of Five Scd Galaxies as Determined from 21-Centimeter Observations[END_REF][START_REF] Rubin | Rotational properties of 21 SC galaxies with a large range of luminosities and radii, from NGC 4605 (R=4kpc) to UGC 2885 (R=122kpc)[END_REF] reveal a flat velocity profile for radii far beyond visible mass concentration. In a Keplerian system, the rotational velocity is expected to fall with the square root of the galactocentric distance r, as in Equation 1.1:

v(r) = GM(r) r (1.1)
where G is the gravitational constant and M(r) is the mass contained in r.

The observed behavior hints at the presence of an additional source of gravitational pull in the galactic outskirts. Essentially, this can be explained either by positing the existence of non-luminous matter interacting gravitationally or non-local effects of gravity (or both, in principle). Figure 1.2 shows the spiral galaxy NGC2403 [START_REF]Image Data: Subaru Telescope (NAOJ) and Hubble Legacy Archive; Processing: Robert Gendler[END_REF] (left) and its rotation curve (right) [START_REF] Begeman | Extended rotation curves of spiral galaxies: dark haloes and modified dynamics[END_REF]. The profile is broken down in three individual mass components: gas, visible-spectrum matter (stars, etc.) and a non-luminous galactic halo component increasing with galactocentric distance. To date, similar behavior has been observed for numerous galactic systems making the galactic rotation curve anomaly a wellestablished piece of evidence for the existence of dark matter (in the broad sense of the term). The profile is broken down in three mass components: gas, visiblespectrum matter (stars, etc.) and a non-luminous galactic halo component increasing with galactocentric distance. Credits: [START_REF]Image Data: Subaru Telescope (NAOJ) and Hubble Legacy Archive; Processing: Robert Gendler[END_REF] (left) and [START_REF] Begeman | Extended rotation curves of spiral galaxies: dark haloes and modified dynamics[END_REF] (right).

Galaxy Clusters

Clusters of galaxies are the largest gravitationally bound systems in the Universe. They can contain thousands of galaxies, in addition to intracluster hot gas emitting X-rays. Earlier in the section, the mass-to-light ratios of Coma and Virgo clusters were mentioned among the first hints for the existence of dark matter. There is other kinds of observations conducted on galaxy clusters that support the latter hypothesis: measurements of the baryonic mass fraction and measurements of the distribution of mass and baryonic matter.

The underlying methodologies are briefly reviewed following [START_REF] Green | Dark Matter in Astrophysics/Cosmology[END_REF].

mass-to-light ratio

The Virial theorem can be applied to gravitationally bound objects such as galaxy clusters. It relates time averages of kinetic and potential energies in the system:

2K + U = 0 (1.2)
Additionally: 2K/M = v 2 , where M is the total cluster mass and v 2 is the average square velocity over all system galaxies. And: U = 1 2 i =j Gm i m j /r ij , with G gravitational constant, m i masses of individual galaxies and r ij distance between galaxies i and j. A gravitational radius can be defined such that: R G = 2M 2 /( i =j m i m j /r ij ). Total cluster mass can thus be estimated as:

M = R G v 2 G (1.3)
since both R G and v 2 are measurable. Luminosity is likewise measurable.

Typical mass-to-light ratios are found to be M/L ∼ 300M /L . Current estimate for Coma is M/L ∼ 250M /L [START_REF] Ryden | Introduction to Cosmology[END_REF].

baryon fraction from hot gas x-rays The fraction of mass contributed by baryons f b = M b /M can be estimated by making few assumptions on the galaxy cluster. The hot intracluster gas contributes the majority of baryonic cluster mass [START_REF] Ryden | Introduction to Cosmology[END_REF]. If the gas is distributed in a spherically symmetric fashion and is in hydrostatic equilibrium, then:

1 ρ dP dr = - GM(r) r 2 (1.4)
Assuming that the gas behaves ideally: P = k B ρT/µm p (µ is the gas mass in units of the proton mass m p ), one has:

k B T µm p d ln T d ln r + d ln ρ d ln r = - GM(r) r (1.5)
X-ray measurements provide knowledge of both terms. In particular, temperature and density can be estimated with X-ray spectroscopy. Mass and radius are extracted by means of X-ray surface brightness measurements [START_REF] Gonzalez | Galaxy cluster baryon fractions revisited[END_REF]. A recent estimate for the baryon fraction extracted using data from twelve galaxy clusters is f b = 0.136(5) [START_REF] Gonzalez | Galaxy cluster baryon fractions revisited[END_REF], with ∼85% remaining mass thus contributed by dark matter.

mass and matter spatial distribution

Massive galaxy clusters deflect light. This effect is called gravitational lensing and results in warped multiple images of the background object (relative to the observer). The spatial distribution and intensity of these images can be used to infer the mass distribution of the galaxy cluster [START_REF] Tyson | Detailed Mass Map of CL 00241654 from Strong Lensing[END_REF].

Colliding clusters such as the Bullet cluster [START_REF] Clowe | A Direct Empirical Proof of the Existence of Dark Matter[END_REF] are the ultimate piece of evidence for dark matter and can be used to constrain its self-interactions. These systems are studied in the visible and X-ray spectra to extract information on the matter distribution. Weak lensing allows to reconstruct the gravitational potential using data in the visible spectrum. X-ray spectroscopy constrains the hot gas spatial distribution. The Bullet cluster is the first of a series of observations showing that in a system of colliding clusters mass and baryonic matter distributions are clearly non-degenerate, with most mass observed around the collision core. The cluster must thus contain significant amount of non-baryonic matter. Recent collision data is shown in Figure 1.3, with gas and mass distributions represented by pink-and blue-shaded regions, respectively. The interpretation of these observations is that weakly self-interacting using visible-light images from HST. Chandra data was used to locate the X-ray emission from intracluster gas (pink shades), constituting the majority of visible matter. Credits: [20] dark matter drives the mass distribution, while hot gas interacts and tends to lag behind. Recent studies on the (particle) dark matter self-interaction cross section using cluster collision data find: σ/m χ ∼ (0.1 -1) cm 2 g -1 [START_REF] Tulin | Dark matter self-interactions and small scale structure[END_REF].

Cosmic Microwave Background

The hot early Universe (k B T > 13.6 eV) is composed of nuclei and electrons.

Forming atoms are constantly ionized, photon scattering being the dominant process. As the Universe cools down expanding, atoms start forming. This occurs when k B T ∼ 0.32 eV (0.25 My), because photons greatly outnumber baryons. Photons scattering rate subsequently drops due to decreasing charge density. Radiation-matter decoupling occurs when k B T ∼ 0.26 eV (0.37 My):

photons start free-streaming across the Universe [START_REF] Green | Dark Matter in Astrophysics/Cosmology[END_REF]. Today, they are constantly detected with microwave antennas. This radiation is the Cosmic Microwave Background (CMB) [START_REF] Penzias | A Measurement of Excess Antenna Temperature at 4080 Mc/s[END_REF]. Due to the continued expansion of the Universe, the CMB is highly red-shifted (z = 1100). The observed spectrum is black-body like, with temperature T 0 = 2.7255(6) K [START_REF] Fixsen | The temperature of the Cosmic Microwave Background[END_REF]. The density fluctuations [START_REF] Smoot | Structure in the COBE Differential Microwave Radiometer First-Year Maps[END_REF] at the time of decoupling are related to structure formation and lead to fluctuations in the temperature distribution of the CMB. These are modeled with the aid of a multipole expansion:

T (ϑ, φ) -T T = ∞ l=1 l m=-l a lm Y m l (ϑ, φ) (1.6)
The CMB power spectrum is defined as the set of expectation values of the square of the expansion coefficients:

C l = |a lm | 2 (1.7)
Small (large) l values correspond to to large (small) angular separations. No dependence on m is considered, since the Universe is assumed isotropic. The CMB power spectrum can be exploited to infer the energy-matter content of the Universe. Recent high-resolution measurements have been performed by the ESA Planck spacecraft [START_REF]Planck 2018 results -VI. Cosmological parameters[END_REF]. The measured power spectrum is shown in Figure 1.5, along with the ΛCDM best-fit curve. ΛCDM (Lambda Cold Dark Matter) is the standard cosmological Big Bang model. It contains three major components: dark energy (Λ), cold dark matter (CDM) and ordinary matter. Dark matter is assumed to be cold (i.e. non relativistic), else it would not cluster gravitationally and form galactic halos. The Planck measurements agree strikingly well with ΛCDM, as suggested by Figure 1.5. In particular, the following values are extracted for dark and baryonic matter relic densities:

    
Ω c h 2 = 0.1200 [START_REF] Rubin | Rotational properties of 21 SC galaxies with a large range of luminosities and radii, from NGC 4605 (R=4kpc) to UGC 2885 (R=122kpc)[END_REF] Ω b h 2 = 0.02237 [START_REF] Green | Dark Matter in Astrophysics/Cosmology[END_REF] (1.8) About 84% of matter is predicted to be dark. The CMB power spectrum thus constitutes further evidence of the existence of cold dark matter.

candidates

The evidence provided in previous section should have convinced the reader that a non-luminous and non-baryonic source of gravitational field is at play in the Universe. As mentioned, the two most natural candidates that can explain these observations are particle dark matter and modified gravity. This thesis work is centered on the former, which is focused on in the following.

As for modified gravity, the first theory thereof -MOND (MOdified Newtonian Dynamics) -was put forward by Milgrom [START_REF] Milgrom | A modification of the Newtonian dynamics as a possible alternative to the hidden mass hypothesis[END_REF]. MOND modifies Newton's second law in the small acceleration regime (a a 0 ) to: F = ma 2 /a 0 (a 0 ∼ 10 -10 m/s 2 ) to match galactic rotation curves. The first formulation of MOND presented many shortcomings, among which violation of basic conservation laws (energy and momentum). Milgrom and Bekenstein first constructed the complete non-relativistic framework AQUAL (A QUAdratic Lagrangian) fulfilling the latter [START_REF] Bekenstein | Does the missing mass problem signal the breakdown of Newtonian gravity?[END_REF]. The TeVeS (Tensor-Vector-Scalar) relativistic extension was later formulated by Bekenstein [START_REF] Bekenstein | Relativistic gravitation theory for the modified Newtonian dynamics paradigm[END_REF]. TeVeS has had some success in reproducing observations at the galactic scale. However, evidence from the galaxy clusters and the CMB power spectrum has been harder to replicate [START_REF] Dodelson | The real problem with MOND[END_REF]. Further evidence disfavoring MOND theories comes from galaxies seemingly lacking dark matter [START_REF] Dokkum | A galaxy lacking dark matter[END_REF] and gravitational waves [START_REF] Boran | GW170817 falsifies dark matter emulators[END_REF]. Despite this, modified gravity remains to date an open possibility for the missing mass anomaly.

Additional dark matter candidates such as baryonic MACHOs (MAssive Compact Halo Objects) and Standard Model neutrinos can not constitute the majority of the missing mass in virtue of the evidence shown in Section 1.1. In particular, the former are constrained by baryon fraction measurements, simulations and lensing studies [START_REF] Gonzalez | Galaxy cluster baryon fractions revisited[END_REF][START_REF] Yoo | The End of the MA-CHO Era: Limits on Halo Dark Matter from Stellar Halo Wide Binaries[END_REF]. Neutrinos would constitute hot dark matter and thus not lead to the galactic halo structure formation.

Particle Dark Matter

Accumulated evidence for dark matter constrains its properties. Dark matter should be [START_REF] Billard | Direct Detection of Dark Matter -APPEC Committee Report[END_REF][START_REF] Baltz | Dark matter candidates[END_REF][START_REF] Thieme | The Low-Energy and Large-Scale Frontier of Dual-Phase Xenon Time Projection Chambers for Dark Matter Search[END_REF]: optically dark (electromagnetically inert), collisionless (not strongly interacting with the SM and itself), cold (non relativistic) and stable (τ > 160 Gy [START_REF] Audren | Strongest model-independent bound on the lifetime of Dark Matter[END_REF]). Optical darkness implies that only very weak interactions with the electromagnetic field are allowed, and as a consequence any properties such as electric charge and EM dipoles must be tiny if not zero. The collisionless property is required to ensure flattened ellipsoidal galactic halos, as opposed to smaller spherical ones. The degree to which self-interactions occur is dictated by the necessary small scale structure erasure in galaxy halos and cores [START_REF] Baltz | Dark matter candidates[END_REF]. One of the reasons why dark matter is expected to be nonrelativistic (and to have been in the early Universe) is structure formation, as mentioned earlier. This, however, does not rule out hot (relativistic since the early Universe) or warm (relativistic then, non relativistic now) dark matter. In fact, some apparent issues with CDM can actually be attenuated by introducing a fraction of its warmer counterpart [START_REF] Billard | Direct Detection of Dark Matter -APPEC Committee Report[END_REF][START_REF] Lovell | The haloes of bright satellite galaxies in a warm dark matter universe[END_REF]. Finally, dark matter cannot possibly decay over timescales shorter than the age of the Universe, since it made it all the way to the present from the radiation-dominated epoch.

The presented constraints are not highly stringent in terms of the variety of acceptable particle candidates. Different production mechanisms (freezeout, asymmetric dark matter, etc.) are possible with a plethora of ensuing different candidates. Two further requirements are that the dark matter relics originate in the early Universe, and that the expected relic density matches the observed value. Figure 1.6 shows the allowed mass range for main particle candidates (about 40 orders of magnitude), with the exception of primordial black holes: a subset of MACHOs potentially contributing to CDM. These candidates can be subdivided based on the intuitive criteria proposed in [START_REF] Pospelov | Cosmological probes of light weakly coupled fields[END_REF][START_REF] Ramanathan | Particles Taking Selfies: Investigations into Light Dark Matter Using Silicon Charge Coupled Devices[END_REF] as: Well-motivated, Why not?, Gap-filling and Unnatural. Well-motivated the range they cover are reported. Adapted from [START_REF] Battaglieri | US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report[END_REF] dark matter particles are WIMPs (Weakly Interacting Massive Particles) [START_REF] Feng | Dark Matter Candidates from Particle Physics and Methods of Detection[END_REF] and QCD axions [START_REF] Gondolo | Dark matter axions revisited[END_REF]. The former are weak-scale (10 -10 4 GeV/c 2 ) candidates desirable by virtue of the Higgs mass problem in particle physics. The axion (10 -9 -10 meV/c 2 ) constitutes a possible solution to strong CP violation in quantum chromodynamics. The Why not? category includes natural candidates that are not motivated by a specific question. Among these: sub-GeV hidden sector dark matter [START_REF] Foot | Dissipative hidden sector dark matter[END_REF][START_REF] Lin | Sub-GeV dark matter models and direct detection[END_REF] and sterile neutrinos [START_REF] Dodelson | Sterile neutrinos as dark matter[END_REF]. The hidden sector is a hypothetical set of particles and interactions akin to the Standard Model, but hardly accessible. An interesting hypothesis posits that it be coupled to the latter through a hidden-SM photon kinetic mixing [START_REF] Postma | Massive hidden photons as lukewarm dark matter[END_REF], which would make it detectable. Right-handed sterile neutrinos arise from the observation of SM neutrino masses and mixing. Adding these, SM neutrinos get mass with the same mechanism as quarks and charged leptons, which provides motivation for their existence. However, strong constraints have been set with only mixing angles as small as sin 2 (2ϑ) 10 -11 still allowed [START_REF] Kopp | Sterile Neutrinos as Dark Matter Candidates[END_REF].

Gap-filling candidates such as ultra-light superfluid (∼eV) [START_REF] Khoury | Dark Matter Superfluidity[END_REF] or fuzzy dark matter (10 -22 -10 -20 eV/c 2 ) [START_REF] Hu | Cold and fuzzy dark matter[END_REF] address galactic scale observations, but are otherwise somewhat unnatural. Finally, highly speculative candidates such as Chameleons (particles coupling to matter more weakly than gravity -see e.g. [START_REF] Khoury | Chameleon cosmology[END_REF]) have no theoretical motivation nor address any observational anomaly and are thus least sought.

In the following, particle candidates the DAMIC experiments are sensitive to are focused on: WIMPs and (some) sub-GeV dark matter.

Thermal WIMPs

Dark matter was produced in the early Universe. Several cosmological mechanisms have been considered for its production (see e.g. [START_REF] Feng | Dark Matter Candidates from Particle Physics and Methods of Detection[END_REF]). WIMPs are thermal relics produced via thermal freeze-out. Dark matter is initially assumed to be in thermal equilibrium with the Standard Model, with high-temperature (k B T m χ c 2 ) 2-to-2 annihilations: χχ ff. Due to expansion cool down, when k B T m χ c 2 , chemical equilibrium is broken, with the SM annihilation rate vanishing (χχ ← ff) and a steady drop in the WIMP number density.

WIMP annihilations continue until freeze out (χχ → ff), where the annihilation rate is equal (comparable) to the Hubble expansion: n FO χ σ ann v ≈ H, with n FO χ WIMP number density at freeze-out. At that point, the WIMP relic density is fixed to today's value: Ω χ h 2 ∼ 0.1 [START_REF] Ruderman | Dark Matter Production[END_REF].

Weakly interacting massive particles are the most popular dark matter candidates due to the so-called WIMP miracle: a numerical coincidence. The DM abundance from thermal freeze-out is extracted solving the Boltzmann equation for n χ . Numerical solutions give the following relic density:

Ω χ h 2 ≈ 6 × 10 -27 cm 3 s -1 σ ann v (1.9)
which is equal to ∼0.1 when weak-scale values are plugged in for the cross section: σ ann ∼ 10 -36 cm 2 and v = 0.1c. This fact is tantalizing in that new particles at the Fermi scale are expected from the SM gauge hierarchy problem too. Figure 1.7 shows the evolution of the thermal weak-scale WIMP relic density in the early Universe. Freeze-out happens at k B T ≈ 4 GeV. for an annihilation cross section that yields the correct relic density, and the shaded regions are for cross sections that differ by 1, 2, and 3 orders of magnitude from this value. The dashed contour is the number density of a particle that remains in thermal equilibrium. Credits: [START_REF] Feng | Dark Matter Candidates from Particle Physics and Methods of Detection[END_REF] As a matter of fact, thermal WIMPs need not be at the weak scale. A simple dimensional analysis yields: σ ann ∼ g 4 /m 2 χ , with g effective WIMP-SM coupling. The correct relic density can be achieved consistently with the freezeout mechanism by keeping the ratio fixed: couplings ranging from gravitational to strong, and masses ranging from ∼1 eV/c 2 to ∼120 TeV/c 2 are allowed [START_REF] Billard | Direct Detection of Dark Matter -APPEC Committee Report[END_REF]. Weak-scale WIMPs have been searched for extensively in the weak mass-cross section parameter space. No definitive evidence for such particles has been found to date. The latest results on WIMP dark matter from the DAMIC at SNOLAB experiment are described in Chapter 3.

Sub-GeV Dark Matter

The sub-GeV dark matter discussed in this thesis is the leptophilic kind, i.e., the one interacting with leptons; in direct dark matter detectors typically bound electrons. In the context of thermal freeze-out production, new mediators below the weak scale are necessary to yield the observed relic density [START_REF] Lin | Sub-GeV dark matter models and direct detection[END_REF].

These are typically assigned to a so-called hidden sector, the simplest example of which is a U(1) gauge group with a hidden photon γ h , whose particles are singlets under the SM gauge group. The hidden photon can be coupled to the Standard Model through the kinetic mixing portal: L ⊃ -(ε/2)F µν F µν h , with ε kinetic mixing parameter and F h U(1) hidden photon field. Dark matter can then be a fermion charged under U(1) (such as a dark electron) [START_REF] Ruderman | Dark Matter Production[END_REF].

Two case-scenarios can be considered: m γ h > m χ and m γ h < m χ . In the former case, direct annihilation (χχ → ff) sets the relic abundance, with masses

m χ
MeV/c 2 . If m γ h < m χ , dark matter can annihilate to its mediator.

Masses m χ keV/c 2 are allowed. In the limit, m γ h = 0, it can be shown that hidden sector dark matter couples to the SM photon with an effective charge εg χ , with g χ dark current gauge coupling [START_REF] Lin | Sub-GeV dark matter models and direct detection[END_REF]. Hidden sector particles in the 1 -10 3 MeV/c 2 range can be produced via freeze-in too. During freeze-in, the dark matter density grows until temperature drops below the mass of the particle responsible for production. The density settles correspondingly.

Freeze-in dark matter from a hidden sector does not require new mediators beyond the Standard Model (which are still a possibility). Millicharged sub-GeV particles thus constitute potential candidates, and, in particular, do not violate optical darkness and collisionlessness requirements.

The search for sub-GeV dark matter has begun only more recently in direct detection experiments. Solid-state detectors such as DAMIC CCDs can witness hidden photon absorptions and inelastic scatterings by fermion/scalar hidden sector particles [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. Chapter 7 details the first hidden sector search with the DAMIC-M prototype experiment.

direct detection of particle dark matter

Dark matter searches are conducted with three types of experiment: production at colliders, indirect detection and direct detection.

production at colliders

Dark matter production is theoretically possible at powerful accelerators such as the Large Hadron Collider (LHC). The maximum dark matter mass that can be produced is set by the available center-of-mass energy. The detection strategy at colliders relies on measurements of the missing transverse momentum p T , given the expected low interaction rate and relatively high background multiplicity. The total transverse momentum is zero, since hadrons are collided head-on in the transverse direction. Any imbalance is then attributed to elusive particles escaping LHC detectors. Standard Model backgrounds and their spectra are known to a very accurate degree, which makes these searches sensitive to tiny distortions in the missing p T spectrum. These capabilities are used to constrain dark matter models [START_REF] Kahlhoefer | Review of LHC dark matter searches[END_REF]. However, if dark matter particles were found with colliders, it would not be possible to assess their stability since they would elude detection before decaying.

indirect detection

Indirect detection searches look for observable products of relic dark matter decays, annihilations and other possible interactions.

To this end, multipurpose instruments such as space telescopes can be leveraged. The numerous available detection channels allow to probe models oth- [START_REF] Marrodán | Dark matter directdetection experiments[END_REF]. The salient addition relative to reference [START_REF] Marrodán | Dark matter directdetection experiments[END_REF] is that shown signal channels all have potential for sub-GeV dark matter detection (see e.g. [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF][START_REF] Derenzo | Direct detection of sub-GeV dark matter with scintillating targets[END_REF]).

erwise inaccessible. The main drawback in indirect searches is presented by the high backgrounds affecting virtually all detection channels [START_REF] Slatyer | Les Houches Lectures on Indirect Detection of Dark Matter[END_REF].

direct detection

Direct dark matter detectors constitute active targets of baryonic matter looking for signals from DM particles in the charge, light and heat channels. The main signatures are nuclear and electron recoils. In particular, traditional WIMP searches look for recoiling nuclei following a coherent WIMP-nucleus scattering. Sub-GeV dark matter detection seeks electron scattering signals instead. Figure 1.9 shows the signal channels of direct detection experiments and the associated detection strategies.

Detectors with charge readout rely on ionization as a working principle.

Atomic electrons of detector constituents are ionized by external radiation and subsequently collected by means of appropriate electric fields to quantify energy deposits. DAMIC at SNOLAB [START_REF] Aguilar-Arevalo | Characterization of the background spectrum in DAMIC at SNOLAB[END_REF] and DAMIC-M [START_REF] Castelló-Mor | DAMIC-M Experiment: Thick, Silicon CCDs to search for Light Dark Matter[END_REF] are ionizationbased direct detection experiments using silicon sensors. Some ionization detectors can also assess the directionality of interactions and exploit Earth's motion across the Milky Way dark matter halo for background discrimination.

Alternatively, any direct detection experiment can seek the expected annual modulation in the rate of events [START_REF] Freese | Colloquium: Annual modulation of dark matter[END_REF].

Light detectors collect scintillation light emitted in de-excitations of detector constituents (typically molecules). Scintillation signals may not always be detected with perfect efficiency. Experiments such as XENONnT [START_REF] Aprile | Projected WIMP sensitivity of the XENONnT dark matter experiment[END_REF] deploy dual-phase TPCs, where scintillation light and ionization charge are complementary. These noble-liquid detectors have pioneered traditional WIMP relics (10 -10 4 GeV/c 2 ) searches. They are now headed towards detecting an irreducible background of neutrinos coherent elastic scatterings [START_REF] Aalbers | DARWIN: towards the ultimate dark matter detector[END_REF]: the notorious neutrino floor [START_REF] Billard | Implication of neutrino backgrounds on the reach of next generation dark matter direct detection experiments[END_REF].

Heat detectors measure thermal excitations. Bolometers detect phonons using detectors at cryogenic temperatures of ∼mK order. Scattering events produce ∼10 meV phonons. Two salient examples of such detectors are CRESST [START_REF] Abdelhameed | First results from the CRESST-III low-mass dark matter program[END_REF], detecting both phonons and scintillation light in CaWO 4 crystals, and Su-perCDMS, using semiconductor crystals (Si and Ge) phonon signal to achieve a lower recoil threshold at the cost of ionization-yield-based discrimination [START_REF]A Strategy for Low-Mass Dark Matter Searches with Cryogenic Detectors in the SuperCDMS SNOLAB Facility[END_REF]. Superfluid bubble chambers such as PICO [START_REF] Amole | Dark matter search results from the complete exposure of the PICO-60 C 3 F 8 bubble chamber[END_REF] use liquid state targets in hyperbaric conditions. Recoiling charged particles generate bubbles (radiationinduced bubble nucleation) which are imaged to reconstruct event topology and energy.

Dark matter direct detection experiments are conducted in underground laboratories in order to minimize cosmogenic backgrounds. Additionally, low radioactivity shielding materials are used to suppress environmental radiation produced in the vicinity of detectors.

Halo Parameters

In order to extract quantitative information on potential dark matter signals such as mass and cross section, (in)direct detection experiments ought to model the expected dark matter flux. The local dark matter density and its velocity distribution provide a full characterization. The former is constrained with observational data [START_REF] Read | The local dark matter density[END_REF]. The typical value used in direct detection experiments is ρ χ = 0.3 GeV/c 2 /cm 3 (Standard Halo Model [START_REF] Green | Astrophysical uncertainties on direct detection experiments[END_REF] and PhystatDM [START_REF] Baxter | Recommended conventions for reporting results from direct dark matter searches[END_REF]). As for the velocity distribution, the usual assumption is that halo dark matter can be considered as a self-gravitating spherically symmetric ideal gas, in which case the Maxwell-Boltzmann distribution applies. For a heliocentric frame of reference [START_REF] Lewin | Review of mathematics, numerical factors, and corrections for dark matter experiments based on elastic nuclear recoil[END_REF]:

f( v) = 1 π 3/2 v 3 0 exp - |v| 2 v 2 0 (1.10)
with v 0 = 2/3σ v most probable speed and σ v standard deviation. The fact that above a given speed v esc dark matter would escape the halo gravitational potential is taken into account by redefining the distribution as follows:

f(v) ∝                exp -(v-v E ) 2 v 2 0 -exp -(v+v E ) 2 v 2 0 v v esc -v E exp -(v-v E ) 2 v 2 0 -exp - v 2 esc v 2 0 v esc -v E < v v esc + v E 0 v > v esc + v E (1.11)
where v E denotes earth velocity in heliocentric frame.

ρ χ v 0 v esc v E (GeV/c 2 /cm

Interaction Rates

Detector properties, dark matter flux and interaction probability determine the event rate in a direct dark matter detection experiment. The following treatment provides basic ideas for the chapters to come. For a rigorous review of these concepts and their nuances reader is urged to consult devoted references such as [START_REF] Marrodán | Dark matter directdetection experiments[END_REF]. What follows applies in general to both WIMPs and sub-GeV dark matter considered later in this work. The overall event rate can be written on dimensional grounds as:

R = N t n χ σ χt v (1.12)
where N t denotes the number of target atoms, n χ = ρ χ /m χ the number density of halo dark matter particles and σ χt v is the speed-averaged product of σ χt dark matter-target (nucleus or electron) interaction cross section and speed. In practice, one is interested in comparing measured and expected recoil energy distributions. The differential rate of events depends on dark matter flux and cross section kinematic dependence:

dR dE R = ρ χ m χ m t v esc v min d 3 vf(v, v E )v dσ χt (E R , v) dE R (1.13)
where m t represents the target mass, with the rate expressed in differential rate units:

1 dru = 1 (keV-kg-day) -1 .
For WIMP-nucleus scattering, the differential cross section is expressed as a sum of a spin-dependent (SD) and a spin-independent (SI) terms:

dσ χt /dE R ∼ σ SD F 2 SD (E R ) + σ SI F 2 SI (E R ).
The spin dependence of interactions can be probed whenever detectors are constituted by isotopes with unpaired nucleons. This is not the case for silicon, thus, only the SI contribution is considered. The recoil energy reads:

E R = v 2 µ(1 -cos ϑ)/m A , where µ = m A m χ /(m A + m χ ) is
the reduced mass of the WIMP-nucleus system and ϑ is the scattering angle in the center-of-mass frame. As an example, this expression yields a maximum recoil energy of about 500 eV in silicon for a 1 GeV/c 2 WIMP. The energy deposited by such recoiling nucleus in e.g. DAMIC at SNOLAB detectors is about 50 eV, which is very close to its threshold. For this reason DAMIC sensitivity rapidly worsens below 1 GeV/c 2 . Figure 1.10 shows differential rates for common direct detection targets: silicon, argon, germanium and xenon, and masses 1, 10 and 100 GeV/c 2 . These rates are computed as in [START_REF] Lewin | Review of mathematics, numerical factors, and corrections for dark matter experiments based on elastic nuclear recoil[END_REF]. The spin-independent WIMP-nucleus scattering cross section can be expressed as:

σ SI = σ χn µ 2 µ 2 n A 2 (1.14)
where the WIMP-nucleon cross section σ χn is used to perform comparisons among different targets. Quantity µ n represents the DM-nucleon reduced mass. The A 2 (target mass number) dependence favors detection with heavier nuclei. As mentioned, no direct detection experiment has found definitive evidence for WIMPs so far. As a consequence, exclusion limits have been set

for a range of about 10 orders of magnitude in σ χn , for weak-scale WIMPs [START_REF] Billard | Implication of neutrino backgrounds on the reach of next generation dark matter direct detection experiments[END_REF][START_REF] Ciaran | New Definition of the Neutrino Floor for Direct Dark Matter Searches[END_REF], where a potential dark matter signal will become hidden underneath coherent elastic neutrino-nucleus scattering.

Semiconductor detectors and bolometers are set to explore a vast portion of the light WIMP parameter space (0.1 -10 GeV/c 2 ). Credits: [START_REF] Billard | Direct Detection of Dark Matter -APPEC Committee Report[END_REF].

A thorough review for sub-GeV dark matter scattering rates in semiconductors can be found in [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. Referring to Equation 1.13, the cross section computation takes into account the momentum dependence on the scattering potential and the target initial-final state transition amplitude, besides the kinematics. For an electronic excitation from generic level 1 to 2 [START_REF] Essig | Direct detection of sub-GeV dark matter[END_REF]:

σ χe v = σe µ 2 χe d 3 q 4π δ ∆E 1→2 + q 2 2m χ -q • v × |F DM (q)| 2 |f 1→2 ( q)| 2 (1.15)
where σe is the DM-free-electron scattering cross section and factors in the interaction strength, q is the associated momentum transfer, F DM is the dark matter form factor encoding momentum dependence, and f 1→2 is the transition amplitude of the electronic states. The general expression for the dark matter form factor is: F DM = αm e /q n . The case n = 0 concerns point like interactions via heavy mediators, the case n = 1 electric dipole coupling, and the case n = 2 interactions via ultra-light (or massless) mediators. The energy scale for these scatterings is that of the ∼eV (for masses 1 -10 4 MeV/c 2 ), which is why experiments able to detect and resolve few-electron signals are most competitive for these specific candidates. Solid-state detectors and bolometers thus lead the search. Sensitivity and limits are typically reported on σe at a reference momentum of about 3.7 keV/c. Figure 1.12 shows sensitivities for heavy mediator dark matter in silicon and germanium targets, assuming different charge thresholds. In this configuration, DAMIC achieved world-leading results on WIMPs [START_REF] Aguilar-Arevalo | Results on Low-Mass Weakly Interacting Massive Particles from an 11 kg d Target Exposure of DAMIC at SNO-LAB[END_REF] and hidden sector dark matter [START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF], and constructed the first comprehensive CCD radioactive background model [START_REF] Aguilar-Arevalo | Characterization of the background spectrum in DAMIC at SNOLAB[END_REF]. The present chapter is subdivided into two main parts. The first part is devoted to describing the functioning principles of the DAMIC detectors, the Charge-Coupled Devices. The second part provides a description of the DAMIC apparatus and a summary of the characterization studies carried out prior to the last science data run, the subject of Chapter 3.

scientific charge-coupled devices

Charge-Coupled Devices are arrays of MOS (metal-oxide-semiconductor) capacitors. They were originally developed in 1969 at AT&T Bell Labs by Willard Boyle and George Smith [START_REF] Boyle | Buried channel charge coupled devices[END_REF], whom were awarded the 2009 Nobel Prize in Physics for their invention. CCDs were initially conceived as memory storage units, and first named Charge Bubble Devices, in analogy with the magnetic bubble memory devices. Their success as ionization imaging sensors came a

the damic experiment at snolab few years later, in the mid-seventies, after Michael Tompsett used them for the first time to acquire digital images [START_REF] Francis | Charge transfer imaging devices[END_REF]. They would be later deployed in many fields of scientific research, notably astronomy, where they are currently the sensors of choice for imaging in the visible portion of the electromagnetic spectrum, but also commercially, where, however, they are gradually being replaced by the CMOS (complementary metal-oxide-semiconductor) active pixel arrays [START_REF]Key differences between CCD and CMOS imaging sensors[END_REF]; noisier but less expensive to produce.

The CCD is a two-dimensional grid of pixels identified by row and column Transfer is completed by moving carriers horizontally across the pixels of the outermost row(s) -the serial register -using serial clocks, towards the sense node, where they are read out and subsequently disposed of. This process occurs for all pixels to be read out.

DAMIC is a direct detection dark matter experiment, so it must be massive, in order to achieve maximal exposure. One way to accomplish that is to use large and thick sensors. DAMIC CCDs measure 6.2 cm×6.2 cm×675 µm, to be contrasted with the few-tens-of-µm thick astronomy CCDs. They feature 4116 × 4128 pixels 15 µm × 15 µm wide, and have a sensitive thickness of 669 ± 3 µm, for a total active mass of 6.0 g. Figure 2.1 shows a DAMIC CCD unit ready to be installed in the DAMIC apparatus.

In the following, the physics of semiconductors is reviewed, in order to provide the foundations to understand how scientific CCDs work. The four functioning stages of a CCD are described in detail subsequently, with particular emphasis on the structural features designed to achieve desired performance.

Working Principles

In scientific CCDs, the pixel MOS semiconducting layer consists of a junction of n-and p-doped materials instead of an intrinsic silicon body. The layer is biased with a substrate voltage, which grants full depletion by removing free carriers. The depleted region constitutes the sensitive volume where signal ionization charge is produced. Joining n-and p-doped layers of adequate extent produces a well-like potential profile at shallow depth ( 1 µm) across the substrate thickness. This region is called buried channel and greatly enhances CCD performance in terms of charge transfer and leakage current relative to early surface-channel CCDs (see e.g. [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]). The properties of the buried channel CCD can be understood through the basics of semiconductor physics. In the rest of this chapter, the discourse will focus on silicon as the semiconductor of choice for DAMIC detectors.

Elements of Semiconductor Physics

The outer-shell atomic electrons in semiconductor crystals form energy bandlike structures, consisting of finely-spaced discrete energy levels electrons can hop on and off of. Such structure is due to the arrangement of atoms in the lattice, which causes wavefunction overlapping. The corresponding degeneracy breaks due to the Pauli principle and leads to closely spaced levels as numerous as the pairs of electrons in the lattice [START_REF] Leo | Techniques for Nuclear and Particle Physics Experiments: A Howto Approach[END_REF]. ing energy level is originated close to the valence band. Thermal energy will suffice to promote neighboring valence electrons to this level, effectively making holes charge carriers in semiconductors.

In an intrinsic semiconductor, the number of electrons in the conduction band is equal to the number of holes in the valence band and they equally contribute to electricity conduction across the crystal. The presence of donor or acceptor impurities alters this balance by introducing mobile charge and energy levels, with a corresponding increase in electrical conductivity. The conductivity (inverse of resistivity) of an intrinsic semiconductor can be written as:

σ = ρ -1 = en i (µ e + µ h ) (2.1)
where e is the elementary charge, n i is the concentration of electrons in the conduction band (which corresponds to the concentration of holes in the valence band for an intrinsic semiconductor) , and µ e and µ h are the mobilities of electrons and holes, factors establishing the proportionality between drift speed and electric field. The above equation states that increasing carrier concentration boosts conductivity. This is the idea behind semiconductor doping:

the controlled introduction of impurities in order to enhance electrical conductivity. The concentration of injected dopants is usually much higher than the intrinsic carrier concentration. In a semiconductor doped with donor impurities (n-type semiconductor) electrons are the majority carriers. In a semiconductor doped with acceptor impurities (p-type), majority carriers are holes in the valence band. The vast majority of electronic devices make use of doped (or extrinsic) semiconductors (e.g., transistors).

the np junction Buried-channel CCDs and most other solid-state detectors are based on the np junction. A np junction is the product of doping a chunk of semiconductor with both donor and acceptor impurities so that gradients in the concentration of the carriers are nonzero and have opposite direction across a shared spatial region (see Figure 2.3). In the case of CCD fabrication, this can be achieved by e.g. ion implantation, exposing the semiconductor to a beam of accelerated ions of the impurity [START_REF] Matalon | Searching for Light Dark Matter with DAMIC at SNO-LAB and DAMIC-M : investigations into Radioactive Backgrounds and Silicon Charge-Coupled Devices[END_REF]. The difference in concentration of electron and holes on the two sides of the crystal initially leads to a diffusive process where mobile charges migrate towards the side where they constitute the minority carriers. This process leads to the steady state depicted in across the junction, the diffusion stops, and the junction comes to a stationary condition. The net effect of this process is the formation of an electrically charged region depleted of mobile charges. The electric field will push out any carrier produced or transiting therein. This is the crucial feature that makes np junctions suitable for radiation detectors. Electron-hole pairs from ionization in the depleted region can be collected to detect ionizing particles and measure their energy. In addition, the junction can be biased with an external voltage to optimize the sensitive volume and charge collection efficiency. If the external electric field has opposite direction with respect to the junction's ( E ext // -E jun -positive terminal on p-side) the biasing is forward. In this case, a net current flow will be observed, as electrons are attracted from the n-side across the junction potential barrier. The converse case ( E ext // E jun -positive terminal on n-side) is said reverse biasing, and has the net effect of widening the depletion region, as both ends of the junction are further depleted of mobile carriers. This corresponds to increasing the available volume for radiation detection. Full depletion across the crystal thickness is achieved with a sufficiently high bias voltage. Going further up can lead to reverse current and damage for the device. The depletion depth on either side of the junction can be found by solving the in-medium Poisson equation in one dimension. The following relations hold [START_REF] Leo | Techniques for Nuclear and Particle Physics Experiments: A Howto Approach[END_REF]:

z n = 2εV 0 eN D (1 + N A /N D ) (2.2) z p = 2εV 0 eN A (1 + N D /N A ) (2.3)
where ε is the electric permittivity of the semiconductor, V 0 is the biasing voltage and N D and N A are the concentrations of donor and acceptor impurities, respectively. For DAMIC p-type buried-channel CCDs, the concentration of acceptor impurities in the p-side is much higher than that of donor impurities on the n-side: N A N D . The overall depletion width then is:

d = z n + z p ≈ 2ε Si V g e 1 N D (2.4)
where V g is the biasing gate voltage responsible for depletion across the junction in the CCD pixel. However, full depletion of the ∼100× thicker n-type layer of substrate still requires application of the substrate voltage, V sub , to the backside of the device. This is also meant to drift carriers towards the buried channel, where they are stored before transfer across the pixel array.

Charge Production -The Photo-Sensitive Volume

The schematics in voltage (> 40 V). Its large depleted thickness results in good quantum efficiency in the near infrared. Above the sensitive volume lies a 1-µm thick layer of boron-doped p-type silicon, which hosts the buried channel: the region where charge is collected and stored, before transfer and readout. A layer of insulator achieved by oxidizing (or nitrogenizing) the surface of the silicon wafer interfaces the p-type layer with polysilicon electrodes. The latter stage is a three-level gate structure, where each of the electrodes constitutes a separate piece of polysilicon, isolated from the others by means of a thermally grown oxide [START_REF] Sequin | Charge-coupled area image sensor using three levels of polysilicon[END_REF]. The substrate voltage is applied on the wafer by means of an ohmic backside contact, made of a thin heavily doped polycrystalline silicon layer capped by indium tin oxide and silicon dioxide layers granting good short-wavelength response [START_REF] Holland | Fully depleted, back-illuminated charge-coupled devices fabricated on high-resistivity silicon[END_REF].

Charge Collection -The Buried Channel measured. While drifting, carriers undergo lateral diffusion in the x and ŷ directions. This can ultimately cause signal charges to be collected in a different pixel with respect to the region where they were produced. Once in the buried channel, charge is held in place relative to the x ŷ (column-row) plane by the three gate voltages (in the row direction) and n-type implants also known as channel stops (in the column direction). Appropriate sequencing of the three gate voltages is used to transfer charge across the CCD. or vice versa raising it to drift the charge out. The three gate voltages are shared across all pixels in a column and the parallel clock sequence is run for all columns. The charge of all pixels is thus transferred in the parallel direc-

V1 V2 V3 V1 V2 V3 h h h h h h h h h h h h

Charge Readout -Reset and Output Transistors

The readout stage of a DAMIC CCD consists of a number of gates and two transistors: the reset switch and the output amplifier. summing well above the level of the output gate permits charge transit. The sense node is a depleted region biased with a reference voltage, V R supplied through the reset switch. Charge measurement is accomplished by capacitive coupling of the output amplifier to the depleted region. When pixel charge Q p approaches the sense node (one end of the capacitor), it induces a µV-order voltage signal ∆V c inversely proportional to the capacitance C SN :

∆V c = Q p /C SN (2.5)
The signal is amplified by means of the output transistor and digitized with a and pedestal (first measurement) substracts out reset pulse noise. In addition, the integration strongly suppresses high-frequency noise contributions.

This approach is referred to as correlated double sampling (CDS). The bottom image of Figure 2.9 shows CDS performed on signals affected by high-and low-frequency noise.

Sources of Noise

Different sources of noise internal and external to the CCD affect the measurement of signal charge in pixels. They can be subdivided in the following categories:

• Output Amplifier Noise ( 10e -) in the CCD, of thermal, environmental and operational origins. CTI occurs when charge is lost (or injected) during transfers across rows and columns. Pick-up noise concerns a variety of external sources of electronic noise: cross-talk, ground loops, electromagnetic interference, etc.

Output Amplifier Noise

Output amplifier noise can be further broken down in distinct components: white, reset, and flicker noise.

White noise stems from thermodynamical fluctuations in the number of the measured charge carriers. It is an increasing function of the temperature, T, and resistance of the output amplifier, R L . It can be expressed in units of electrons as [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]:

σ white = √ 4k B BT R L S SN × A amp (2.6)
where k B is the Boltzmann constant in jK -1 , B is the noise power bandwidth, S SN is the sensitivity of the sense node measured in V/e -, and A amp is the output amplifier gain.

Reset noise was already touched upon in Section 2.1.1. It is produced by the recurrent reset of the sense node reference voltage and it translates to the fact that the reference level is different from pixel to pixel. Reset noise also has thermal origin, and thus has a similar expression as white noise: on the temperature and the nature of defects. It is this mobile charge that induces the flicker noise [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF][START_REF] Alers | Tunneling current noise in thin gate oxides[END_REF]. The larger contribution at low frequencies is explained considering that long-lived states fluctuations do not cancel out over a one measurement period, while shorter-lived processes tend to [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF].

σ reset = √ k B T e ×
The arguments exposed in Figure 2.9 show that flicker noise cannot be suppressed by CDS, thus it sets the output amplifier noise floor. Figure 2.10 shows qualitative trends for white and flicker noise frequency spectra.

Dark Counts

The term dark counts broadly refers to all processes that produce few-electron events across the CCD. There is a variety of such processes:

• Intrinsic Dark Current • Extrinsic Dark Current • Glowing (Amplifier Light) • Clock-Induced Charge (CIC).
Intrinsic dark current (or leakage current) refers to carriers generated thermally in the device. The energy-level structure in semiconductors was discussed in Section 2.1.1. The minimum amount of energy necessary to excite an electron from valence to conduction band in silicon is 1.16 eV, which is available thermally even at cryogenic temperatures. Additionally, impurity-or defect-introduced energy levels are in closer proximity to conduction and valence bands, which facilitates thermal excitations. Thermally produced carriers are collected in pixels, thus contributing to overall noise. Intrinsic dark current can be further subdivided in surface and bulk contributions. The surface contribution typically dominates, and stems primarily from silicon-silicon oxide interface states. The majority of bulk dark current is attributable to lattice defects and impurities in the substrate of the CCD [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]. Since the electronhole pair thermal generation probability follows ∼T 1.5

exp [-E g /(2k B T )] [86],
intrinsic dark current is reduced by lowering the detector temperature. This is why DAMIC CCDs are operated at T 140 K.

Extrinsic dark current refers to environmental sources of low-energy events that result in few-electron signals [START_REF] Barak | SENSEI: Characterization of Single-Electron Events Using a Skipper Charge-Coupled Device[END_REF]. These depend on the operating venue and the detector materials. Some known contributions to extrinsic dark current are Cherenkov, transition and recombination radiation induced by highenergy backgrounds in the surroundings of the detector [START_REF] Du | Sources of Low-Energy Events in Low-Threshold Dark-Matter and Neutrino Detectors[END_REF]. The dark counts contributions quoted above are proportional to the CCD operation times: thermal, environmental and amplifier light counts all increase linearly with time. Clock-induced charge is produced as a result of CCD clocking. As such, it only depends on the number of transfers a given pixel undergoes.

Charge Transfer Inefficiency

Charge can be left behind during transfers. This will cause the measured pixel charge to differ from its original value. CTI can be caused by insufficient clock swings (i.e., the difference between low and high clock rails), but also defects and mechanical stress in the CCD (e.g., as induced by very low temperature).

Pick-up Noise

Pick-up noise comes from external sources of electromagnetic field. For instance, devices in the surroundings or part of the apparatus itself might be radio emitters. Detectors must be protected from such external disturbances.

Typical solutions involve EM shielding, grounding connections and electrical insulation. Ultimately, it is impossible to prevent all EM noise to seep in. However, effective configurations can be found such that the dominant con-tributions come from CCD readout or control electronics and are thus to be considered irreducible (without dedicated R&D).

CCD Data

CCD image acquisition consists of two main phases: exposure and readout. Exposure refers to the period over which all clocks remain idle, in accumulation phase for ionization charge. Readout refers to the period during which charge transfer and pixel readout occur. After exposure, pixels are read out and their values digitized by means of a 16-bit ADC. The corresponding value can range between 0 and 2 16 -1 analog-to-digital units (ADU). This information is transmitted via optical fibers to the DAQ machine, where it is stored in the form of a FITS (Flexible Image Transport System) file. The image size is user-defined and it need not be equal or smaller than the physical size of the CCD. The fraction of image acquired past the vertical and/or horizontal size of the CCD is referred to as overscan. Vertical and horizontal overscans are differentiated by the exposure history of their pixels, although in no case they participate in the exposure phase of data acquisition. The vertical overscan pixels go through a number of parallel transfers equal to the number of rows in the CCD plus a number of serial transfers equal to their column index (the coordinate index starts at 0). Horizontal overscan pixels, instead, are only exposed for a number of serial transfers equal to the column size of the image.

In both cases, two further transfers occur at readout: when charge is moved in and out of the summing well.

Images should be visually inspected when testing CCDs. The inspection can spot anomalies such as hot regions, 5 glowing and pedestal fluctuations. The first data processing step is producing the histogram of image pixel values, the pixel value distribution (PVD). The moments of this distribution provide information on pixel pedestal, readout noise and dark current. Any external background events introduce high-charge entries in the PVD, complicating the process of extraction. It is thus desirable to acquire low background data for detector characterization. If this is not possible (e.g., at shallow sites), a practical alternative is using overscan datasets. These have negligible exposure times and are much lower background. A background-free PVD follows a Gaussian law if the CCD behaves correctly. Its mean provides an estimate for the pedestal level and its standard deviation corresponds to the readout noise within uncertainties. The pixel value after pedestal subtraction is pro- Data follows a Gaussian law in ±3σ range. Readout noise is ∼1.9 electrons. Few entries with charge 9 e -from energetic events are visible. portional to its charge content. The distribution of pedestal-subtracted pixel values is referred to as pixel charge distribution (PCD). This term is used indiscriminately for pedestal-subtracted values expressed in ADU or electron units.

In order to convert pixel values from ADU to electron (or energy) units6 a calibration campaign must be conducted (see Section 2.2.1). Figure 2.13 shows the calibrated PCD for a DAMIC CCD low-background image, characterized by low noise of 1.9 electrons.

Charge from high-energy events ( 1 keV) appears in the form of two dimensional particle tracks: clusters of pixels. The topology of a track depends on the ionizing particle depositing energy in the CCD, its kinetic energy and the spatial distribution of the depositions. In particular, interaction depth determines diffusion, i.e., track lateral spread. Figure 2.14 shows an example of DAMIC CCD image with distinct tracks, and a reference image with typical event topologies. In order to reconstruct clusters and extract the total deposited energy, it is necessary to design an algorithm capable of efficiently locating sets of neighboring pixels with an overall charge amount incompatible with noise. This algorithm is referred to as clustering. DAMIC devised two different strategies for this purpose: seed clustering and likelihood clustering.

These will be discussed in depth in Chapter 3, along with other methodologies to optimize CCD noise and event reconstruction efficiency.

the damic detector

The DArk Matter In CCDs experiment at the SNOLAB underground laboratory sits beneath 2 km of granite, and deploys optimized ancient lead and polyethylene shielding. In its final form, the detector consists of an array of

seven

Detector Calibrations

DAMIC detectors have been extensively tested and characterized before acquiring science data. In particular, distinct calibration runs were performed to characterize charge diffusion, energy response and dark current. These campaigns will be only touched upon to provide foundations for Chapter 3.

The reader is encouraged to examine references [START_REF] Aguilar-Arevalo | Characterization of the background spectrum in DAMIC at SNOLAB[END_REF][START_REF] Chavarria | DAMIC at SNOLAB[END_REF][START_REF] Aguilar-Arevalo | Search for low-mass WIMPs in a 0.6 kg day exposure of the DAMIC experiment at SNOLAB[END_REF] for exhaustive descriptions.

Depth Calibration

DAMIC CCDs enable the spatial reconstruction of energy depositions in three dimensions. The interaction position in the horizontal plane is known by virtue of the pixel structure. The vertical coordinate must be inferred by build- ing a diffusion model that relates event depth to the lateral spread of the associated event cluster. Figure 2.16 illustrates charge diffusion from a point-like energy deposition in a CCD with xẑ and x ŷ (pixel plane) cross-sectional views.

According to [START_REF] Holland | Fully depleted, back-illuminated charge-coupled devices fabricated on high-resistivity silicon[END_REF][START_REF] Groom | Point-spread function in depleted and partially depleted CCDs[END_REF], charge from a point-like energy deposition at depth z is distributed in the x ŷ pixel plane as a 2D Gaussian with equal variance in both directions:

σ 2 xy (z) = -A ln |1 -bz| (2.8) with:      A = 2ε Si k B T ρ n e b = ε Si V b ρ n z D + z D 2 -1
(2.9)

where ε Si is the silicon permittivity at operating temperature, ρ n is the donor charge density, V b is the potential difference between charge-collection well and CCD backside, and z D is the CCD active thickness. Diffusion parameters can be computed using theoretical expressions of Equation 2.9, but it is preferable to estimate them experimentally. The most natural way to do that is making use of tracks produced by minimum ionizing particles (MIP) that pierce through the entire CCD thickness, such as cosmic muons. Data acquired with 1 × 1 binning is ideal for this task, as it retains all spatial information. The DAMIC depth calibration run was carried out at Fermilab, at shallow depth, to profit from a significant muon flux. As shown in the bottom of Figure 2.14, it is possible to infer the location of track endpoints, since that is where the MIP enters the front (z = 0) and exits the back (z = z D ) of the CCD active region. Interaction depth can be estimated for the entire track. This is done rigorously by maximizing the log-likelihood of the (set of) tracks as a set of point-like interactions, with diffusion parameters unconstrained:

ln L µ = N i=0 ln f q (q i |A, b, M) (2.10)
Here, f q (q i ) represents the probability of measuring charge q i for the i-th pixel along the muon track M, convolved with the two-dimensional Gaussian profile. The diffusion model extracted with this procedure is:

A = 285 ± 24 µm 2 , b = 8.2 ± 0.3 × 10 -4 µm -1 (2.11)
These values are roughly compatible with theoretical expectations from Equation 2.9. Further investigation on 1 × 100 binned data from the most recent DAMIC science run revealed a linear energy dependence for the point-like interaction cluster spread, relative to the theoretical model:

σ x (z) = -A ln |1 -bz| • (α + βE) (2.12)
The observed deviation was parametrized by fitting a linear function to the maximum observed spread as a function of energy in the 2-14 keV energy region. The resulting additional parameters were extracted to be α = 0.956 and β = 1/170.0 keV -1 . Figure 2.17 script in the plot labels refers to electron-equivalent energy. This energy scale measures the ionization caused by photoelectrons, and is used as reference in DAMIC analyses. Recoiled nuclei have different ionization efficiencies; their energy can be converted to the electron-equivalent scale to work with a single energy unit.

Energy Response

DAMIC CCDs energy response was initially evaluated on surface using Xray fluorescence from Al, Cr, Fe, Mn, O and Si for energies 1 keV ee . The low-energy response was investigated later at SNOLAB, using visible photons from a red light-emitting diode (LED). Definitive calibration constants were obtained with copper and lead fluorescence lines from parts of the DAMIC at SNOLAB apparatus. The top plot in Figure 2.18 shows the fluorescence spectrum acquired on surface with a 55 Fe X-ray source. The bottom plot summarizes linearity measurements conducted on surface and underground. Xray data additionally enabled resolution measurements. A value of 54 eV ee at 5.9 keV ee was obtained, corresponding to a Fano factor of 0.133 ± 0.005 [START_REF] Aguilar-Arevalo | Search for low-mass WIMPs in a 0.6 kg day exposure of the DAMIC experiment at SNOLAB[END_REF]. 9 The Fano factor used in the latest DAMIC results is F = 0.129, as more recently measured in [START_REF] Ramanathan | Measurement of low energy ionization signals from Compton scattering in a charge-coupled device dark matter detector[END_REF].

linearity. energy calibration

The LED campaign at SNOLAB studied response linearity at lower energies; specifically, between 40 eV ee and 70 eV ee . The LED was installed inside the vessel, on the VIB board. Optical photons of ∼700 nm wavelength (about 2 eV) were used since they produce one single electron-hole pair. Images with 20 s exposure to LED light were acquired. The calibration methodology relies on the Poisson nature of the charge measured in a pixel exposed to constant illumination, with rate given by the average number of photons impinging on a pixel, Nγ . The calibration constant k e can be extracted as (see [START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]):

k e = 1 3.8 eV ee σ 2 l µ l (2.13)
if the readout variance is negligible compared to the pixel value variance, which is the case when the Poisson rate is high enough [START_REF] Lapeyrere | Calibration of flight model CCDs for CoRoT mission[END_REF]. Parameters µ l 9 The Fano factor takes into account the constraint introduced in stochastic energy loss when the total energy deposited in the detector, E d , is fixed. When E d is not fixed, the number of eh pairs it produces follows a Poisson law, and the resolution reads:

R(E d ) = FWHM(E d )/E d = 2.35 • √ N/N,
where N is the mean number of eh pairs. When E d is fixed, however, the Poisson assumption breaks down. The Fano factor is the multiplicative and σ 2 l are pixel charge distribution mean and variance in ADU units. The factor 1/3.8 eV -1 ee is included to normalize the constant to units of e -/ADU. Note that the ionization energies of the red points in Figure 2.18 do not correspond to the LED energy. Rather, the analysis strategy of this work allowed to calibrate DAMIC CCDs down to the energy thresholds driven by cluster reconstruction, and demonstrate the energy response linearity within their operating range. The interested reader is invited to look at [START_REF] Ramanathan | Particles Taking Selfies: Investigations into Light Dark Matter Using Silicon Charge Coupled Devices[END_REF].

quantity F such that R(E d ) = 2.35 • F • √ N/N.
Calibration constants for the seven operational DAMIC CCDs were extracted using copper and lead fluorescence lines from parts of the setup. The final values are reported in Table 2

nuclear recoil ionization efficiency

The signal of recoiled silicon nuclei following a hypothetical WIMP-nucleus interaction is feeble compared to the energy deposition by an electron of the same energy. 10 The nuclear recoil ionization efficiency (NRIE) relates the ionization signal observed in the detector in units of eV ee to the recoiled nucleus kinetic energy in units of eV nr . 11 It is essential to know the NRIE to translate the observed signal into the energy of the recoiled nucleus. DAMIC performed measurements of the NRIE between 0.7 keV nr and 2.3 keV nr ; previously available measurements went down to 3.0 keV nr [START_REF] Chavarria | Measurement of the ionization produced by sub-keV silicon nuclear recoils in a CCD dark matter detector[END_REF]. The measurement was done by exposing a CCD to a 124 Sb-9 Be photoneutron source. The 124 Sb beta-decays to an excited state of 124 Te, which goes through a de-excitation chain of gamma decays. The predominant decay radiation is a photon of 1691 keV, which disintegrates the 9 Be nucleus as follows: 9 Be(γ, n)2α. The neutrons from this reaction are nearly monochromatic, and they induce nuclear recoils in the CCD, that deposit a fraction of energy through ionization. The reader is encouraged to look at [START_REF] Chavarria | Measurement of the ionization produced by sub-keV silicon nuclear recoils in a CCD dark matter detector[END_REF] for a thorough description of setup and analysis methods. The measurement relied on simulations performed using MCNP [START_REF]Los Alamos National Laboratory[END_REF], and it consisted in

Dark Current Measurements

Minimizing dark counts is critical to achieve high sensitivity to hidden sector dark matter. Intrinsic dark current (DC) usually dominates relative to other components when operating scientific CCDs. Its contribution can be extracted by fitting the PCD to a convolution of a Gaussian function, which encodes output noise, and a Poisson function, which encodes the dark current time dependence. The Poisson rate extracted with the fit gives an estimate of the intrinsic dark current in the CCD. In particular, the pixel charge distribution can be parametrized as: where p is the pixel value, N pixels is the number of pixels in the dataset, n q is the number of charges in the pixel, λ is the dark current rate parameter, k e is the gain, µ ped is the pedestal and σ ro is the pixel readout noise. In order to estimate dark current in this fashion, it is preferable to mask pixel clusters and their surroundings to reduce contributions from extrinsic DC and CTI.

Π(p) = N pixels +∞ n q =0 P(n q |λ)G(p -nk e |µ ped , σ ro ) (2.14) CCD 1 CCD 2 CCD 3 CCD 4 CCD 5 CCD 6 CCD 7

data acquisition and processing

The second stage of DAMIC at SNOLAB started in 2017, aiming for a 100 g scale detector, that is, eighteen CCDs as described in Section 2.1. Eight CCDs could ultimately be deployed. Extension 5 had to be disabled shortly after deployment due to intense amplifier luminescence affecting other sensors, too.

The seven remaining devices were operated with a substrate voltage of 70 V. 1. Digitizer pedestal removal.

Since installation in

The column median 2 is estimated for all columns and subtracted to all pixels in the column. To eliminate any pedestal contribution along individual rows, the same method is adopted across the whole image, in 1029-pixel row segments.

Correlated noise removal.

Pick-up noise from the electronics chain affects all amplifiers. Figure 3.1 displays a portion of two-amplifier image with high correlated noise visible on both sides as a diagonal pattern. Correlated noise can be subtracted out. This is done by subtracting to each given pixel the weighted average of the corresponding pixel in mirror images from all CCDs, with weights evaluated to minimize the pixel variance. This procedure is referred to as correlated noise subtraction and it reduces readout noise by 15%, from 1.9 to 1.6 electrons.

Image calibration.

Resulting images are calibrated to energy units using LED/X-ray results outlined in Section 2.2.1. Conversion from energy to charge is done usnoise from distinct pixels. Therefore, while it implies loss of spatial information, binning is ideal to conduct a particle search. 2 The median is used in order to discard outliers, i.e., charged pixels.

ing a mean electron-hole ionization potential of 3.8 eV ee . An average calibration constant of 0.257 eV ee ADU -1 is obtained for the 7 CCDs.

Data selection.

Data presenting undesired features is discarded. In the course of data acquisition, shifters flag images with high noise for elimination. Horizontal CTI is confirmed to be less than 1%, following 4116 transfers across the entire serial register. Images at the start of each data run have strong dark current transients and are eliminated. 3 Radon levels surrounding the copper vessel are monitored with a Rad7. A set of 441 images (63 exposures) with an average reading greater than 5 Bq/m 3 are excluded. Further 29 images are eliminated because they contain pixels with highly negative values such that: p < -5σ ro . The total CCD live time after data selection is 307 days. Additionally, columns from 0 to 128 and from 3978 to 4116, and rows 1 and 42, are excluded to cut out noise transients. This leaves 5.78 cm in x and 6.0 cm in ŷ, resulting in a 5.6 g CCD target mass (6.6% of pixels removed).

Masking.

Regions with localized high dark current are rejected by defining masks.

Masks

Clustering.

Clustering is performed post-masking to measure energy and cluster spread (σ x ). 4 Only charged pixels that do not border with masks are 3 DAMIC data is split into data runs: stable acquisition periods halted by temperature or power cycles caused by power cuts at SNOLAB. 4 As a consequence of the aggressive ×100 parallel downsampling reducing most events to single-row clusters, only the horizontal spread σ x is considered. These procedures exhaust the DAMIC data processing pipeline and enable the representation of DAMIC data as an energy-cluster spread distribution. Cluster spread range is 0-1.4 pixels. Energy range is 0-6 keV ee . Events detected by CCD 1 and CCDs 2-7 are displayed in different colors.

Seed Clustering

Seed clustering is one of the two algorithms developed in DAMIC. It is preferentially used to locate high-energy clusters, since its reconstruction efficiency rapidly drops below 400 eV ee . The algorithm consists of the following steps:

1. Locate pixels such that p > 4σ ro ( 24 eV ee ).

Group up sets of contiguous pixels found at point 1.

All clusters with an energy content less than 100 keV ee are fitted to a twodimensional gaussian function in order to extract spread and energy. The best-fit Gaussian area is required to be equal to the sum of the cluster pixel values with a 5% tolerance. The fit log-likelihood is required to be negative and compatible with other values found for similar energy clusters.

Likelihood Clustering

Likelihood clustering is conceived to reconstruct point-like ionization events: it looks for depositions contained in a pixel window of predefined size. For this reason, it is most efficient for energies below 10 keV ee . Two quantities are computed for every candidate: the likelihood that the pixel values are described by white noise, L n , and the likelihood that the pixel values are described by a one-dimensional Gaussian, f G , and white noise, L G .

L n = N pixels n=1 1 2πσ 2 w × e -p 2 2σ 2 w (3.1) f G (x, µ x , σ x ) = N e 2πσ 2 x × e - (x-µx) 2 2σ 2 x (3.2)
The log-likelihood ratio quantifies the significance that the cluster stems from an ionization event as opposed to noise only:

∆LL = -ln L G L n (3.3)
where N e constitutes the total charge inside the window, µ x is the coordinate weighed average inside the window, and σ 2 x its variance. These quantities are kept as free parameters in the fit, while for σ w the readout noise value is plugged in. The algorithm is iterated across images on a row-by-row basis, computing for each window (at least of five pixels wide) ∆LL. Clusters are located when ∆LL is sufficiently negative. N e estimates the total charge, σ x measures the lateral spread. The corresponding log-likelihood ratio is stored. Clusters with ∆LL < -22 are deemed ionization events and carried over. Pixels bordering masks are not included in the clustering dataset. Clusters with overlapping windows, spanning 2 or more rows, and with non-Gaussian spatial charge distributions (not point-like) are eliminated. Likelihood clustering reconstruction efficiency is around 90% from 10 keV ee down to about 120 eV ee , where it starts dropping rapidly. The analysis energy threshold is set to 50 eV ee , where efficiency is less than 10%. In this analysis, likelihood clustering is run after seed clustering. All clusters reconstructed with the latter with E > 10 keV ee are masked. The 200 pixels past the cluster in the serial direction are also masked to remove any CTI events. Figure 3.5 shows reconstruction efficiencies for seed and likelihood clustering algorithms. The energy range endpoints, 50 eV ee and 10 keV ee , rep-resent the efficiency-driven threshold for this analysis, and the "switch" point where events are reconstructed only with seed clustering.

detector modeling and background rejection

The DAMIC background model is constructed using measurements and simulations of radioactivity within its apparatus. Assays are conducted to characterize the nature and levels of contamination across the various detector parts.

Importantly, DAMIC CCDs offer a unique opportunity to quantify certain in-sensor contaminants. This is leveraged to inform and constrain the background model. Particle decay and tracking are simulated in a virtual replica of the apparatus using the GEANT4 simulation toolkit [START_REF] Allison | Recent developments in Geant4[END_REF]. CCD response effects are applied on the simulation output. an important detector response peculiarity and the largest source of systematic uncertainty in this analysis, is described in Section 3.2.5. These contents pave the way for Section 3.3, where the construction of the background model is detailed.

Sources of Background in DAMIC at SNOLAB

The following background sources are relevant for the DAMIC at SNOLAB detector:

• Primordial Chains.

The long-lived radioisotopes along the primordial 238 U and 232 Th chains, as well as 40 K. They are widely found in nature and are introduced in detector parts across the different stages of the procurement-deployment pipeline. Secular equilibrium can be broken for certain segments of the chain. These need be considered independently. Radon-222 is an impor-tant example, and will be discussed in the context of surface contamination.

• Cosmic Activation.

High-energy cosmogenic neutrons can induce spallation of nuclei in detector parts resulting in the production of radioisotopes in the material [START_REF] Cebrián | Cosmogenic activation of materials[END_REF]. Cosmogenic activation is effectively reduced minimizing the time detector materials spend on surface or higher altitudes. For instance, ancient lead parts were recovered from sunken ships and spent a minor fraction of time above ground since being retrieved. Their content in cosmogenic isotopes is expected to be significantly less than copper and silicon parts. Silicon isotope 32 Si is an interesting exception: it is produced by activation of 40 Ar in Earth's atmosphere and subsequently transported to ground by precipitations. Consequently, silicon found on surface has higher concentrations of 32 Si relative to silicon mined deep underground, thus preferable for low-background applications.

• Surface Contamination.

Surface contamination refers to 210 Pb and its daughter 210 Bi, as a consequence of radon plate-out on detector materials. One of the radionuclides produced along the primordial uranium chain is 222 Rn, a volatile noble gas with lifetime long enough (t 1/2 = 3.8 days) to travel large distances away from the production site. As a result, 222 Rn is present in Earth's atmosphere and materials are constantly exposed to its decay products. The long-lived 210 Pb (t 1/2 = 22.3 years) is invariably found in detector parts and is a primary radioactive contaminant in DAMIC at SNOLAB. As a result of the sequence of decays preceding it, 210 Pb can be found up to 100 nm into material surfaces. Its decay rate is difficult to constrain with mass spectrometry because of its low abundance, while its decay products are too low-energy for γ-ray counters [START_REF] Bunker | Evaluation and mitigation of trace 210Pb contamination on copper surfaces[END_REF]. However, the 2-beta decay sequence can be observed within reasonable timescales.

This fact is exploited in DAMIC to set constraints on the 210 Pb content in CCDs.

• Cosmic Muons.

Cosmic radiation flux is suppressed by a factor ∼5 × 10 7 going from sea level to underground operation at SNOLAB [START_REF] Snolab | SNOLAB User's Handbook and Web Resources[END_REF]. The cosmic muon flux at SNOLAB of 0.27 m -2 d -1 [START_REF] Snolab | SNOLAB User's Handbook and Web Resources[END_REF] is equivalent to 1 muon crossing the CCD tower every ∼103 days.

• Environmental Neutrons.

Environmental neutrons induce nuclear recoils that mimic the expected WIMP signal. Dedicated measurements [START_REF] Lawson | Low Background Measurement Capabilities at SNOLAB[END_REF] show that there are three main sources of neutrons at SNOLAB: X(α, n)Y reactions involving light nuclei (∼90%), spontaneous fission of Uranium (∼10%), and spallation by cosmic muons interacting with the cavern walls (∼0.1%). The neutron flux is measured to be about 4000 m -2 day -1 for thermal and for fast neutrons [START_REF] Jauregui | Neutron Backgrounds at SNOLAB[END_REF]. Additionally, neutrons are produced in the apparatus through nuclear reactions between light nuclei and alpha particles produced by primordial chains. The major neutron contributor in the setup was shown to be the VIB electronic board [START_REF] Machado | [END_REF].

Background Model Constraints

The activity of several detector contaminants was measured. Assays were mostly focused on primordial chains and were carried out with Inductively-Coupled Mass Spectrometry (ICP-MS), Glow Discharge Mass Spectrometry (GDMS) and Germanium γ-spectrometry at the SNOLAB γ-ray counting facility. Some other components were characterized in precedence or by other collaborations. Table 3.1 reports activity values used to constrain the background model. The upper limit for 210 Pb in the CCD is the only value not used as a constraint. The 210 Pb activity in the copper module screws does not come from a direct measurement. The brass screws value is assumed to be equal to the one in OFHC copper to show that this results in a negligible event rate in the detector (< 0.1 dru). 5 All assays conducted on the CCDs silicon were outperformed by the measurements carried out with the CCD themselves (see Section 3.2.4), except for 40 K.

Activation levels are estimated for copper parts (vessel, box and CCD modules) by taking into account their exposure history. The electroformed copper box of Ext. 1 is assumed radiopure. The average cosmogenic activity during the run is quantified as:

A = S λ∆t run (1 -e -λ∆t act )(e -λ∆t cool )(1 -e -λ∆t run ) (3.4)
where S is the isotope sea-level saturation activity [START_REF] Laubenstein | Cosmogenic radionuclides in metals as indicator for sea level exposure history[END_REF],6 λ = ln 2/t 1/2 its decay constant, and ∆t act , ∆t cool and ∆t run , the activation, cool-down and run times, respectively [START_REF] Baudis | Cosmogenic activation of xenon and copper[END_REF]. Activation times of modules, box, and vessel are 8 months, 16 months, and 1000 years. Cooldown times are 540 days, 300 5 The dru unit (differential rate unit) is employed to measure background rates:

1 dru = 1kg -1 d -1 keV ee -1 . Part\Isotope 238 U 226 Ra CCD < 11 [104] < 5.3 [104]
Kapton cable 58000 ± 5000 [M] 4900 ± 5700 [G] OHFC Cu < 120 [M] < 130 [G] Module screws 16000 ± 44000 [G] < 138 [G] Ancient Pb < 23 [START_REF] Orrell | Assay methods for 238U, 232Th, and 210Pb in lead and calibration of 210Bi bremsstrahlung emission from lead[END_REF] < 260 [G] Outer Pb

< 13 [112] < 200 [G] Part\Isotope 210 Pb 232 Th CCD < 160 [104] < 7.3 [104]
Kapton cable NM 3200 ± 500 [M] OHFC Cu 27000 ± 8000 [START_REF] Abe | Identification of 210Pb and 210Po in the bulk of copper samples with a low-background alpha particle counter[END_REF] < 41 [M] Module screws 27000 ± 8000 2300 ± 1600 [G] Ancient Pb 33000 ± 10000 [START_REF] Orrell | Assay methods for 238U, 232Th, and 210Pb in lead and calibration of 210Bi bremsstrahlung emission from lead[END_REF] 2.3 ± 0.1 [START_REF] Orrell | Assay methods for 238U, 232Th, and 210Pb in lead and calibration of 210Bi bremsstrahlung emission from lead[END_REF] Outer Pb days, and 6.6 years. Run time is 441 days. The vessel activation time is conservatively assumed to be 1000 years, since its history above ground before fabrication is unknown. This assumption is used to demonstrate that its contribution is negligible (< 0.7 dru). This information is used to produce an estimated activity for the following copper activation isotopes: 60 Co, 59 Fe, 58 Co, 57 Co, 56 Co, 54 Mn and 46 Sc. Silicon activation is harder to quantify due to significant uncertainty in exposure history, including altitude variations.

(19 ± 5) × 10 6 [112] < 4.6 [112] Part\Isotope 40 K 32 Si CCD < 0.5 [M] 140 ± 30 [104] Kapton cable 29000 ± 2000 [M] NA OHFC Cu < 31 [M] NA Module screws 28000 ± 15000 [G] NA Ancient Pb < 5.8 [M] NA Outer Pb < 220 [112] NA
The activities of its cosmogenic contaminants, 3 H and 22 Na, are left unconstrained. The 32 Si content is quantified with the CCDs themselves instead, as detailed in Section 3.2.4.

The degree to which CCDs have been exposed to radon plate-out is not well known, but is expected to be the same for all device. Silicon wafers were stored vertically for several years prior to CCD fabrication, exposed to air. A 10 µm layer was etched away from the front surface during manufacturing.

The back surface was not reserved a similar treatment. A higher concentration of 210 Pb is thus expected in the last few µm's of the wafer. After fabrication, CCDs are never stored upside down, thus a larger contamination level is expected on the front surface. Front-and back-surface contaminants are left unconstrained in the background model fit. Lead and copper surfaces in proximity with the sensors are chemically cleaned, eliminating few µm's.

Any surface contamination is expected to be removed by this process. This hypothesis is supported by tests conducted in the construction of the background model: no surface contributions other than silicon wafer and CCD are included.

A cosmic muon making it all the way to DAMIC CCDs at SNOLAB would have mean kinetic energy > 300 GeV [START_REF] Mei | Muon-induced background study for underground laboratories[END_REF] and trigger an important particle shower in the detector, with numerous clusters coinciding in multiple CCDs.

Such high-multiplicity events were not detected in the WIMP search run: cosmic muons can be neglected as a source of background.

Environmental neutrons can be produced externally or internally to the setup. Dedicated studies have demonstrated neutrons to be a negligible source of background for DAMIC, with either source leading to less than one nuclear recoil over the WIMP search exposure. These studies will be delved into in the following Section 3.2.3.

GEANT4 Simulations

At the beginning of his doctorate, author took over a simulation framework based on the GEANT4 toolkit constructed by former DAMIC member J. Da Rocha [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF]. These simulations provide the physical energy-depth spectrum, which is then applied detector response effects and fed to the same processing pipeline as data to reproduce the expected E-σ x distributions from DAMIC at SNOLAB radioactive backgrounds. In this section, the simulation framework is reviewed and results are discussed, primarily focusing on author's contributions. A comprehensive description of the framework and the work conducted to validate it can be found in [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF] and [START_REF] Thomas | Cameras in the Dark: Direct Detection of Dark Matter with Charge-Coupled Devices[END_REF].

GEANT4 is an open source framework consisting of a set of C++ libraries including tools to simulate radiation-matter interactions. It is the framework of choice for major scientific institutions such as CERN and ESA. The three main inputs needed to carry out simulations with GEANT4 are: a virtual geometry model of the apparatus where particles are produced and deposit energy, the particles themselves (radioactive nuclei and their decay products, particles produced from a source, etc.), and the physics models that characterize their interactions with the apparatus materials -the so-called physics lists.

The DAMIC at SNOLAB GEANT4 Geometry

The DAMIC at SNOLAB GEANT4 geometry was constructed by J. Da Rocha, with upgrades and refinements implemented by author. The model was built according to mechanical schematics produced by Fermilab engineer G. Derylo. Volumes are given physical properties by assigning them materials. Simple materials are available in the GEANT4 database: the constituent chemical element is partitioned over its different isotopes with weights according to the respective natural abundance. Composite materials, if not available, can be defined by user. In DAMIC simulations, composite materials had to be defined for two volumes only: the Kapton signal cables, and the VIB board. 7The simulated background spectrum is quite sensitive to the way the CCDs are modeled.

ccd structure in geant4

The CCDs in the GEANT4 model are an accurate reproduction of the physical CCDs of DAMIC at SNOLAB. The gettering layer is the backside electrode where substrate voltage is administered. During manufacture it is heavily doped with phosphorous (n+) which diffuses into the sensitive region. This is shown in the secondary ion mass spectrometry (SIMS) measurements in Figure 3.9. The phosphorous concentration is up to 9 orders of magnitude higher in the last few micrometers of the CCD bulk relative to the fully-depleted region (∼10 11 × cm -3 ). This leads to carrier recombination during drifting, inducing a partial collection of ionization charge (PCC) in the back of the CCD. This effect is the largest source of systematic uncertainty of this analysis. It will be addressed in Section 3.2.5.

The results of SIMS of Figure 3.9 are in slight tension with the simulated backside structure. However, the uncertainty in the PCC region is expected to absorb most of the discrepancy. Both measurements of Figure 3.9 show a high hydrogen concentration in the ISDP region around 2 µm. This is an undesired feature thought to originate during getter deposition where hydrogenrich gases silane and phosphine are employed [START_REF] Pejnefors | Hydrogen in undoped and heavily in situ phosphorus doped silicon films deposited using disilane and phosphine[END_REF]. The tritium trace content of hydrogen constitutes a potential background for DAMIC CCDs. The ISDP layer estimated activity (based on SIMS results) is on the order of ∼mBq/kg.

However, given the getter feeble mass, less than one decay per month is expected. Additionally, simulations show that a minor fraction of tritium beta decay electrons make it all the way to the full collection region. This source of background is not included in DAMIC's model.

The DAMIC at SNOLAB GEANT4 Physics

The basic GEANT4 simulation consists in the following. A user-defined particle is simulated with initial position and momentum and tracked as it traverses materials, thereby depositing energy. A single simulation is called event.

A set of events is called run. The particle path is called track and a track seg- ment step. Energy loss is simulated over three stages by means of the Process class: when the particle is at rest (e.g., decay), across a step (e.g., Cherenkov), and post-step (e.g., scattering). One type of process can be described using different models, which determine the final state following a specific interaction. Processes and models characterizing the energy loss for a given particle are contained in physics lists. GEANT4 offers general physics lists that can be used for any particle and material, for wide ranges of energy. The physics list of choice for DAMIC simulations is Livermore [START_REF] Hubbell | EPDL97: The Evaluated Photo Data Library '97 Version[END_REF][START_REF] Cullen | Tables and Graphs of Electron-Interaction Cross Sections from 10 eV to 100 GeV Derived from the LLNL Evaluated Electron Data Library (EEDL)[END_REF][START_REF] Chen | Tables and Graphs of Atomic Subshell and Relaxation Data Derived from the LLNL Evaluated Atomic Data Library (EADL)[END_REF]. Livermore is particularly suited to describe low energy ( 1 MeV) electromagnetic interactions, since it takes into account the atomic shell structure. It was validated down to 10 eV for electron energy depositions [START_REF]Low Energy Electromagnetic Physics -Livermore[END_REF] and 100 eV for photon cross sections [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF][START_REF] Thomas | Cameras in the Dark: Direct Detection of Dark Matter with Charge-Coupled Devices[END_REF]. A variety of processes lead to the production of secondary particles (e.g., photoelectrons). This is regulated using range cuts: particles whose energy at production is insufficient to travel a given distance are not simulated. Such condition can optimize simulation efficiency. Energy balance is tracked by subtracting the secondary particles contribution at the continuous stage of the process. In DAMIC, cuts have been optimized on a detector volume basis, taking into account volume size and distance from the CCDs.

The range cut for the copper vessel and all volumes outside it is set to 1 mm.

For volumes inside the vessel and outside the copper box, the cut is set to 100 µm. The copper box and its contents excluding the CCDs are assigned a range cut of 1.3 µm. The CCDs have a range cut of 50 nm (electron energy 20 eV [START_REF] Bethe | Bremsformel für Elektronen relativistischer Geschwindigkeit[END_REF]). The latter cut is validated by the results of [START_REF] Lazarakis | Investigation of track structure and condensed history physics models for applications in radiation dosimetry on a micro and nano scale in Geant4[END_REF] (see [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF]).

Radioactive Backgrounds Simulations

The isotopes simulated for the background model construction belong to the first two categories listed in Section 3. DAMIC GEANT4 simulations output consists of several pieces of information, salient among which are coordinates and energy value for each step along all tracks of all events in a run. 8 Output is compressed to reduce its size by up to an order of magnitude, retaining only necessary information to construct the E-σ x spectrum. The compression is done by condensing information from same-track steps that are less than 150 nm apart, and occur within the same CCD.

Neutrons Simulations

There is few sources of neutrons at SNOLAB: X(α, n)Y reactions involving light nuclei (∼90%), spontaneous fission of uranium-238 (∼10%) and spallation by cosmic muons (∼0.1%). Additionally, neutrons are produced in the setup as products of X(α, n)Y, where X and Y are also light nuclei. The major contributor in the setup is the VIB electronic board. To account for these sources of background, two sets of simulations have been carried out, quantifying the expected number of neutron-induced nuclear recoils during the WIMP search exposure.

The first set studied the impact of environmental neutrons, simulating their interactions with polyethylene and lead shielding [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF]. Secondary electrons, positrons and photons are originated and constitute potential background for the CCDs. However, simulations show that the majority of particles that make it through the shielding are neutrons. This is shown in Figure 3.12.

The corresponding upper limit for the number of neutrons crossing the seven sensors during the WIMP search exposure is 5.6 ± 0.5. 9 On the other hand, the probability of neutron interaction with the CCDs is estimated to be 0.13 per neutron, which leads to an expectation of 5.6 n × 0.13 n -1 < 1 scattering events over the WIMP search.

The second set of simulations estimates the number of neutrons produced in the VIB board interacting with the CCDs. Extensive work conducted on neutrons from the apparatus [START_REF] Machado | [END_REF] shows that alpha particles from uranium and thorium chains are the dominant contributors. Figure 3.13 compares neutron production rates from 238 U spontaneous fission (top) and alpha-induced neutron ejection (bottom) in different components of the detector. In both Figure 3.12: Spectrum of primary neutrons and other secondary particles that make it through polyethylene and lead shielding. Plot taken from [START_REF] Miguel | Recherche de matière sombre légère avec des CCDs de l'expérience DAMIC à Snolab[END_REF]. cases the VIB contribution dominates, being several orders of magnitude larger than other detector parts. Furthermore, it produces about an order of magnitude more neutrons due to alpha-induced reactions than from uranium fission below 4 MeV. Given these results, neutrons from the apparatus are demonstrated to be a subdominant background source, showing that those produced in the VIB lead to a negligible number of events over the WIMP search exposure. The VIB board was only simulated for this study. Given its convoluted design, it was simulated as a 1 kg box made of FR4 [126], with dimensions such that the entirety of its features (connectors, bolts, etc.) would be contained in it. pected number of detected events during the 332.5 days of the WIMP search exposure thus is:

N det n = 332.5 d × 10 33333 d ≈ 0.1 (3.5)
Thus, less than 1 neutron-induced nuclear recoil is expected from the VIB board. Given the subdominance of all other detector components, it is concluded that apparatus neutrons constitute a negligible source of backgrounds.

Measurement of CCD Bulk Contaminants

The excellent spatial resolution of CCDs is leveraged to identify and quantify the amount of certain radioactive contaminants they carry. Spatially correlated events with energy and time separation in optimal selection intervals are ascribed to different decay chains. 32 Si and 210 Pb have half-lives compatible with the experiment timescales and can be quantified with this strategy.

This work is thoroughly detailed in [START_REF] Aguilar-Arevalo | Measurement of the bulk radioactive contamination of detector-grade silicon with DAMIC at SNOLAB[END_REF]; in the present section, the salient results and in particular author contributions will be described. The analysis was performed using 1 × 1 data acquired between February and September High-sensitivity constraints are set on bulk silicon contaminants 32 Si and 210 Pb. 10 These are described in the following. Uranium and thorium chains activities are also studied, achieving sensitivities comparable to mass spectrometry. The details of the latter analysis are reported in [START_REF] Aguilar-Arevalo | Measurement of the bulk radioactive contamination of detector-grade silicon with DAMIC at SNOLAB[END_REF]. 10 While high 210 Pb contamination is not expected in the CCD bulk, given the ubiquity of uranium-chain isotopes and in particular radon, it is reasonable to assume it is nonzero.

A = N pairs -N acc -N overlap (ε sel × ε t )m∆t (3.6)
where N pairs is the number of coincident pairs fitting the selection cuts, N acc is the expected number of accidental spatial coincidences, N overlap is the expected number of overlapping events from other decay chains, ε sel is the selection efficiency for a specific search, ε t is the time efficiency of the search as due to image readout and powercuts at SNOLAB, and m∆t is the total exposure (6.5 kg-day for this search) as given by total sensitive mass times exposure time.

Partial Charge Collection

The high phosphorous concentration in the backside of the wafer (see Fig- (see [START_REF] Aguilar-Arevalo | Characterization of the background spectrum in DAMIC at SNOLAB[END_REF]), simulating carrier diffusion, drift and recombination as functions of phosphorous concentration. Figure 3.17

f(E|β) = Ne - √ E/β (3.7)
where the amplitude N depends on the specific PCC parameters. These studies show that the spectral difference is dominated by the model offset, with the slope parameter having secondary impact. The PCC parametrization is incorporated in the likelihood analysis conducted to search for WIMPs (see Section 3.3.2) in order to account for the introduced uncertainty.

background model and wimp search

The Low-statistics simulations (background rate < 0.1 kg -1 d -1 ) are discarded.

Energy-sigma histograms are constructed for each template, using bin widths of 0.25 keV ee in E and 0.025 pixels in σ x (from 0.1 to 1.2 pixels). For a given template, l, the number of expected events ν ijl in bin ij reads:

ν ijl = m n ijm × A l M m (ε data t run ) (ε sim N m ) (3.8)
The sum is computed for each detector volume over the number of events n ijm from simulations, normalized by activity of the given template, A l , mass of simulated detector volume, M m , efficiency-corrected data exposure, (ε data t run ), and efficiency-corrected number of simulated decays, (ε sim N m ). 12The observed number of events k ij in corresponding bin ij is compared to the corrected number of events from simulation ν ij . The latter is obtained as a linear combination over templates:

ν ij = l C l ν ijl (3.9)
The C l coefficients fully characterize the background model, providing the relative contribution of a given template. The two-dimensional log-likelihood is calculated as the sum over all energy and sigma bins, assuming the bin content follows a Poisson distribution with an expectation ν ij . Penalty terms are included to constrain the model according to assay results. It reads: The good agreement between data and model for CCD 1 constitutes further validation of this methodology. Both projections show that in-CCD contaminants bring the highest contribution to the model. Near-detector copper parts come next. A general decreasing trend with distance from the CCDs is observed, as expected. Figure 3.19 highlights contributors to front and backside backgrounds. CCD surface lead-210 dominates. For CCDs 2-7, the second contribution comes from copper modules, which is foreseeable given their proximity to the CCDs. This is expectedly not the case for CCD 1, whose module is made of highly radiopure electroformed copper. Table 3

ln L = ij k ij ln(ν ij ) -ν ij -ln(k ij !) - n (C n -C 0 n ) 2 2σ 2 n (3.
f s (E, σ x |ε) = 1 ε e -E/ε × R(E, σ x ) (3.11)
where R(E, σ x ) is obtained by simulating events uniformly in energy and sigma, applying detector response and reconstructing them with likelihood

clustering. An unbinned extended likelihood function is utilized for the search in order to constrain the overall normalization [START_REF] Barlow | Extended maximum likelihood[END_REF]. The fit is done jointly on the CCD 1 and 2-7 datasets, each having N k events over an exposure fraction γ k . The silicon fluorescence region between 1.6 keV ee and 1.8 keV ee is excluded from the fit. The log-likelihood reads:

ln L(s, ε, b, c) = 2 k -γ k s -b k -c k + N k i (γ k sf s + b k f b k + c k f c + P k ) (3.12) where f s (E i , σ xi |ε), f b k (E i , σ xi ) and f c (E i , σ xi ) represent the signal, back-
ground and the strictly-additive partial charge collection PDFs, respectively. 14 Correspondingly, γ k s, b k and c k are the signal and background events attributed to dataset k. Finally,

P k = (b k -b k ) 2 2σ 2 b k
represent the penalties intro- 13 These same images are used for the background model construction since dark current has no effect above 6 keV ee . 14 The background model is split into two components (f b k and f c ) to thoroughly account for the PCC systematic uncertainty. The PCC correction pdf f c is proportional to the right-hand side term of Equation 3.7 and is strictly additive.

duced by constraining the number of background events. The negative loglikelihood is minimized using MINUIT with amplitudes b k , c k , s, and ε as free parameters. The distribution of observed events is found to be consistent with a background-only scenario down to 200 eV ee , a sign of thoroughness of the developed background model. This is shown in Figure 3.20. Below 200 eV ee , the fit exhibits a preference for a 17.1 ± 7.6 events exponential bulk component (ε = 67 ± 37 eV ee ), with a p-value of 2.2 × 10 -4 (3.7σ). The best-fit PCC offset on the back side of the original wafer is 0.75 +0.50 -0.35 µm, consistent with X-ray calibration results in [START_REF] Fernandez Moroni | Charge-Collection Efficiency in Back-Illuminated Charge-Coupled Devices[END_REF]. Figure 3.21 shows data points in blue overlaid on the best-fit background model in gray for E ∈ [0, 1] keV ee .

Red contours represent the observed excess, with corresponding fraction of events they contain.

Several hypothetical explanations for the excess have been explored, particularly focusing on the systematic uncertainties affecting the analysis. The following checks were conducted:

• Fit above 200 eV ee .

The result of performing the fit above 200 eV ee is consistent with the background only hypothesis.

• Separate fit to CCD 1 and CCDs 2-7.

Individually fitting the two datasets results in both cases in a signal statistically consistent with the result of the joint fit. This signal is more significant for CCD 1, consistent with the fact that this CCD is in a lower background environment.

• PCC uncertainty.

The observed excess is driven by low-sigma (frontside) events (see Fig- No plausible origin for the excess was found among the sources of systematic uncertainty. This finding will be further investigated with the upgrade to DAMIC-M skipper CCDs (see Chapter 4). CCDs and custom electronics are set to radically reduce the readout noise on pixel charge measurement. Sub-electron (or single-electron) resolution levels will be achieved. Sub-electron resolution enables ∼10 eV ee energy thresholds, with a prominent gain in sensitivity at low candidate masses through improved energy resolution and cluster reconstruction efficiency. DAMIC-M will be deployed in 2024 and will acquire a kg-year scale exposure to search for light WIMPs. Hidden sector candidates will also be sought for, retaining competitiveness for datasets with much smaller exposure. The experiment is currently in the fourth year of R&D and has seen substantial progress since inception. In particular, the prototype LBC detector has been deployed in the end of 2021, with the goal of informing DAMIC-M design and logistics. The LBC has intermediate background goals with respect to DAMIC and DAMIC-M, aiming for O(1 dru) rates. In spite of its low mass (about 18 g), it is a competitive dark matter experiment, as will be seen in Chapter 7.

The most important novelty in DAMIC-M is the introduction of the skipper readout amplifier. This technology enables non destructive charge measurements (NDCM) of the pixel charge (also known as skips), thus allowing an arbitrary reduction of the corresponding statistical uncertainty. 1 Given its impact on DAMIC-M science reach, next Section 4.1.1 is devoted to the skipper CCD.

Skipper CCDs

The skipper readout amplifier was proposed by Janesick et al. "for ultra lowsignal level imaging and spectroscopy applications that require sub-electron read noise floors" [START_REF] Janesick | New advancements in charge-coupled device technology: subelectron noise and 4096 x 4096 pixel CCDs[END_REF]. The key distinction between conventional and skipper CCDs is at the output stage. Conventional CCDs use the so-called floating diffusion gate. Floating refers to the fact that the sense node is electrically isolated from the buried channel. The sense node is formed by heavy p-doping of the n-type substrate, which grants the formation of a high-resistivity diffusion region. An ohmic contact is placed directly onto it. When a charge packet makes its way towards the gate, it induces a voltage signal in the sense node through capacitive coupling. Charge is then discarded closing the reset switch, which sets the potential in the buried channel to the reference voltage, V R . Skipper CCDs use the floating gate [START_REF] Wen | Design and operation of a floating gate amplifier[END_REF]. Floating gates employ a metal contact embedded in a layer of dielectric (typically silicon oxide) deposited on the buried channel. The charge packet is still sensed capacitively and the measurement is absolutely non-destructive. Repeated measurements are accomplished with key modifications to the output stage. The output gate is a clock, as opposed to conventional CCDs, where it is a fixed bias voltage.

The reset transistor is only meant to set the sense node back to the reference voltage (V R ) after charge readout. Its role as charge drain is taken over by the dump gate (DG) clock and the drain bias voltage (V drain ). These come into play at the end of the NDCM routine. Figure 4.2 illustrates the NDCM working principle of a skipper amplifier. As a clock, the output gate can be lowered after charge gets integrated in the sense node, to let it back into the summing well (in its low state). Meanwhile, the dump gate is held high to prevent charge from being drained. Carriers can be moved back and forth to the sense node an arbitrary number of times. After the last non-destructive measurement, the dump gate is lowered and charge is disposed of through the drain.

V SR SR SW OG SN VR h h h h h h
σ avg (N skips ) = σ ro N skips (4.1)
where σ ro is the resolution for a single non-destructive charge measurement.

The DAMIC-M Detector

The DAMIC-M experiment will be constructed and operated at the Modane underground laboratory, in France. The laboratory facilities are located halfway through the 13-km Fréjus tunnel at the French-Italian border. This represents an improvement in logistics relative to SNOLAB, where a more complex access procedure is in place. 400 m -2 d -1 depending on the specific location inside the lab [START_REF] Palusova | Natural radionuclides as background sources in the Modane underground laboratory[END_REF], so it is at least one order of magnitude lower than SNOLAB. Radon activity concentration measurements range from 5 to 20 Bq/m 3 as per DAMIC-M and [START_REF] Loaiza | Laboratoire Souterraine de Modane[END_REF].

DAMIC-M will be deployed in a 4.2 m × 4.7 m ISO class 5 clean room where the LBC prototype detector is currently operated (see Chapter 6). An additional low-particulate environment will be set up towards the end of 2022 for underground CCD probing, packaging and testing. 3 The DAMIC-M detector will deploy about two-hundred 6k × 1.5k skipper CCDs, with a sensitive mass of ∼3.5 g each. In order to achieve dru-fraction background rates, detector and shielding design is informed with GEANT4 simulations [START_REF] De | Search for Light Dark Matter with the DAMIC-M Experiment[END_REF], while material handling is carefully foreplanned to minimize contamination levels.

The final DAMIC-M apparatus will feature the elements shown in Figure 4.7, although important differences in terms of design are foreseen. CCDs will 3 CCD probing consists in preliminary electrical measurements to assess the quality of the unpackaged CCD. Packaging refers to the set of procedures that make the CCD unit deployable: on-package gluing, wirebonding, etc. These activities will be carried out underground, in a radon free environment in order to minimize cosmic activation and surface contamination.

DAMIC-M Science Goals

As previously stated, the goal of DAMIC-M is to reach a 1 kg-year order expo- the field. 4 The top plot in Figure 4.9 shows projections for the spin-independent WIMP-nucleus scattering cross section for nuclear recoil (dashed) and Migdal electrons (dotted) signals. 5 The bottom plot in Figure 4.9 reports the sensitivity forecast on the hidden-photon kinetic mixing parameter. Plots in Fig- In the light mediator case, the thick solid line in yellow represents the expected cross section for freeze-in. In all four cases, an improvement up to few orders of magnitude in sensitivity is predicted relative to the current best upper limits. 4 DAMIC at SNOLAB has set world-class exclusion limits on hidden sector dark matter.

The interested reader can consult [START_REF] Aguilar-Arevalo | First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB[END_REF][START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF]. 5 The Migdal effect can be described as recoil-induced atomic ionization [START_REF] Ibe | Migdal effect in dark matter direct detection experiments[END_REF][START_REF] Knapen | Migdal Effect in Semiconductors[END_REF]. When a nucleus is recoiled, its atomic electrons initially lag behind and for sufficiently energetic scatterings ionization is possible.

r&d towards damic-m science goals

The DAMIC-M research and development efforts can be subdivided into three main categories: CCD yield optimization, background reduction and custom electronics. In the following, salient aspects of these activities are discussed, particularly focusing on the evolution of designs and procedures and the underlying motivations.

CCD Yield Optimization

CCD fabrication is a complex process involving a number of high precision steps whose success ultimately determines the performance of the device.

DAMIC-M skipper CCDs must be science-grade; in other words fulfill the following requirements on:

• Working amplifiers.

All DAMIC-M CCDs carry four 47/6 skipper amplifiers. In order to be deployed in the experiment any one CCD must have at least one fully functional skipper amplifier.

• Track imaging.

DAMIC-M skipper CCDs must be able to efficiently collect charge from energy depositions in the buried channel (i.e., be fully depleted) and read it out.

• Defects/Dark current.

Science-grade devices can only feature minor defects (e.g. few hot pixels or columns). Dark current across the device must not exceed the ∼10 -3 e -/pixel/d scale.

• Single-electron resolution.

Single electrons are resolved by performing hundreds of non-destructive charge measurements. The amplifier noise must not exceed few electrons.

• Charge transfer efficiency.

Charge transfer inefficiency must not be greater than ∼1 part in 10 6 .

Note that this includes skip CTI, i.e., the possibility of charge being lost between skips.

• Energy response.

CCD must have linear energy response up to several tens of keV. If a CCD has no working amplifier, cannot properly image tracks or features major defects as shown in Figure 4.11, then it will not undergo extensive testing. Such devices can nevertheless be useful in the commissioning of test chambers (e.g., cryogenics set-up) and basic testing of control/readout electronics. CCDs that fulfill the latter requirements, but only partially others on the above list are engineering-grade. These CCDs can be tested extensively and much useful information can be extracted. In general, if a CCD is engineering-grade, it also means that its manufacturing was mostly successful and small adjustments should be implemented to craft a science-grade device.

The yield of science CCDs is highly dependent on manufacturing. Besides the conventional process flow, DAMIC-M CCDs are subject to measures conceived to minimize in-detector contaminants. The main stages of the fabrication process of DAMIC-M CCDs are reported in Figure 4.12. Each of these steps is described next.

CCD Fabrication

The first step in CCD fabrication is silicon procurement. DAMIC-M n-doped high-resistivity silicon ingots are produced at TOPSIL-GlobalWafers in Denmark [150]. In general, the ingot production starts with silica sand (SiO 2 ), which is converted to metallurgical-grade polycrystalline silicon and then purified by means of different chemical processes to obtain a part-per-billion Once the impurity-collection process is done, the getter can in principle be ground away for replacement with a thinner (∼20 nm) ISDP layer, whose sole purpose is serving as backside contact. This is not a common procedure in CCD manufacturing, but would suppress tritium and the PCC region. Backside removal is under study in the pre-production runs and could be implemented for the production batch. Note that while Figure 4.12 suggests removal is performed using a grinding wheel, several options are being considered for DAMIC-M CCDs. After backside processing, wafers will be diced into the chosen format.

Originally, DAMIC-M CCDs were designed to be 6k × 6k in format; however, consultations with DALSA indicated 6k × 1.5k (6144 × 1536) as an optimal compromise between size and yield at the production stage. Such format was thus chosen. Figure 4.13 shows a diced pre-production wafer into four main 6k × 1.5k dice. The dice lot is sent to LSM, where cold probing is conducted. This includes DC probing checks looking for shorts across the device, but also more in-depth testing of device response to electromagnetic stimuli. DAMIC-M will deploy a dedicated probe station to carry out these tests.

CCDs will be packaged in the same low-particulate environment. Sensor and signal cable will be glued onto a silicon substrate, wirebonded and installed in an aluminum package. The CCD will then be ready for deployment for testing/characterization sessions.

In view of the complex journey that DAMIC-M CCDs are supposed to undergo before deployment, pre-production batches of CCDs are manufactured to establish the production process flow and single out any process responsible for a reduction in yield.

Pre-production Status

The first 32 DAMIC-M pre-production CCDs were packaged at the University of Washington (UW) between September and December 2021. Packaging protocols demonstrated effective with previous LBNL CCDs were followed. The CCD testing was carried out at the University of Chicago and UW. LPNHE contributed to establish a CCD testing protocol using R&D science-grade CCDs. This work will be detailed in Chapter 5. Pre-production run 1 (PP1) results were not satisfactory to proceed with production. This was not unexpected, since some procedures specific to DAMIC-M thick CCDs were carried out for the first time. Results can be summarized as follows:

• Visual and microscopic inspections found no issue with the sensors.

• 30 out of 32 CCDs have at least a working amplifier (WA).

• WA single-skip noise is as expected for test systems (∼5e -).

• WA noise decreases as ∼1/ N skips . Single electron resolution is achieved by performing a few hundreds of skips.

• No CTI appears in WA images. Although not quantified precisely, it is expected to fulfill science-grade requirement.

• Major defects (up to pixel saturation) are present in all CCDs.

As of the last bullet point, no PP1 CCD could be considered science-grade. to PP1, where some steps were carried out at LBNL, with consequent additional logistics. Unlike PP1, no DC probing will be conducted prior to packaging, since during the first run it resulted in damage for few CCDs. The results of PP2 will be critical for DAMIC-M, although at least another pre-production run is possible to understand and correct the origin of the issue.

Background Mitigation

The DAMIC-M background mitigation campaign mainly focuses on material selection and handling, and detector design. In the following, a summary on the status of these subjects is provided.

Material Selection and Handling

DAMIC-M detector parts, especially those in proximity to the CCDs, must be low radioactivity. To this end, radiopure materials are selected for DAMIC-M apparatus. Additionally, activation must be minimized. DAMIC-M have put into place special protocols to achieve this. The DAMIC at SNOLAB analysis showed that more than half (55%) the observed background rates can be ascribed to the CCDs themselves. Tritium is the dominant contamination in DAMIC CCDs, contributing an average 31% of the overall background rates between 1 and 6 keV ee . Surface lead-210 and bulk silicon-32 follow. Previous section discussed backside processing as a measure to eliminate backside tritium. However, the bulk activation component brings the dominant contribution. Lead-210 abounds on wafer and CCD surfaces and originates from radon plate-out during fabrication and storage. Silicon-32 seeps into the CCD production chain at its very beginning, as a trace isotope in silica sand. The following measures are taken to minimize these contaminants:

• Low-altitude transportation and underground storage.

Detector Design

The DAMIC-M detector design evolved considerably since inception. Modifications were driven by GEANT4 simulations detailed in [START_REF] De | Search for Light Dark Matter with the DAMIC-M Experiment[END_REF], and mainly concerned the design of the cryostat with its cooling system and CCD stack.

DAMIC-M cryostat must comply with mechanical and cryogenic conditions.

In addition, its design and the disposition of detector parts inside it should be optimized in terms of backgrounds. The CCD stack with its IR copper shield are accommodated in one arm of an L-shaped structure, whose other extremity contains cooling pipes in thermal contact with a heat exchanger located right above the CCD stack. This shape is meant to locate the sensitive detector and cryogenic/electronic components out of each other lines of sight, with a corresponding decrease in background contribution. Figure 4.18 shows the initial and final (preliminary) DAMIC-M inner apparatus designs. In sum- and module unit (bottom) design. In particular, 13 modules will be deployed on each arm of the cross geometry EFCu holder, for a total of 52 modules.

Each module will accommodate four sensors. The CCDs will be glued onto a silicon pitch adaptor and a single flex cable will transport control and video signals for all four.

Custom Electronics

In order to have full flexibility on operational parameters, reduce electronic noise and broaden the dynamic range of pixel values ad hoc electronics will control and read out independently each DAMIC-M module (i.e., 4 CCDs).

The control part will enable tuning of individual clocks (width, rise time and amplitude) and biases (amplitude) delivered according to a specific sequencer The detector room area is 12.5 m 2 . The gowning room is equipped with a dresser with drawers for personal protective equipment. The detector room is subject to frequent configuration changes but always contains a wide variety of worktools (screwdrivers, allen keys, etc.), electrostatic-discharge (ESD) safe equipment (mats, wrist straps, chairs, etc.), cleaning solutions (IPA and ethanol), dry nitrogen for cryostat flushing and cleaning, the test CCDs in ESD-safe boxes and spare electronics components. All equipment entering the cleanroom is cleaned using IPA or ethanol and gaseous nitrogen (if need be). Powder-free gloves and lint-free wipes are used for the cleaning. A sticky mat is placed next to the gowning room entrance, in order to remove any debris from shoes. Shoe-covers are subsequently worn inside the gowning room, The orange cryostat is used for CCD testing and LPNHE-electronics development. The latter work will not be discussed in this thesis. More details can be found in [START_REF] Papadopoulos | Development and characterization of novel electronics for the search of dark matter for DAMIC-M[END_REF]. The blue cryostat test system was constructed and commissioned to a satisfactory degree of completeness, as detailed in the following sections.

Cryogenics

The blue cryostat cryogenics consists of chamber, vacuum control system and temperature control system. The blue aluminum cryostat is a 12 × 12 × Vacuum Products [START_REF]Ideal Vacuum Products[END_REF]. It was assembled inside the clean room. High-vacuum is made inside the cryostat using an Agilent TPS-compact pumping station equipped with a floating suspension turbomolecular pump and AVC run on a 48 V linear power supply to minimize noise. The cooler is operated in power control mode (one can also control cold head temperature). A Lakeshore germanium RTD monitors the cold head temperature. The heat rejector temperature is also measured as a safety parameter. Figure 5.4

shows the air-side elements of the blue cryostat test system cryogenics: cryostat, vacuum pump, pressure gauges, and cryocooler. The only instrument not appearing is the Lakeshore 325 temperature controller.

Cryogenics Testing

The cryogenic system was tested extensively before detector installation. Pump was verified to reach nominal rotation speed of 70000 rpm to obtain pressures 10 -4 mbar. Any significant leaks were identified and corrected by gradually extending the vacuum chain from pump to cryostat, or by isolating suspect parts. Highly volatile high-purity ethanol was also used to assess the presence of leaks: slight amounts of liquid were administered to suspect joints across the chain. More sophisticated means such as helium leak testing were also available but unnecessary in that satisfactory levels of vacuum were reached from the onset. After breaking vacuum (e.g for CCD installation), percent-level outgassing spikes were typically observed at low pressure (P 10 -4 mbar), indicating release of trapped gas from the inner walls of cryostat and other components of the chain. A faster decrease rate was always measured soon after starting the cryocooler, due to the deceleration and increased adhesion of gas molecules to cryostat surfaces. Conversely, an outgassing spike was always observed when switching off cryocooler. Vacuum levels in the chamber were initially consistent with pump specifications (O(10 -6 mbar) at cryogenic temperatures). However, the pump unexpectedly failed in January 2021, after which, despite preserving functionality, levels of ∼10 -5 mbar were only attainable. The reasons of these failures were investigated inconclusively. It was nevertheless decided to continue operations.

Ad hoc safety software was produced to protect the detector against these events (see Section 5.2.2). Figure 5.5 shows the typical pressure evolution inside the chamber as measured by the cryostat pressure gauge. Cryocooler cold head temperature evolution is reported as well to correlate the two variables. Chamber pressure is initially around ∼1 × 10 2 mbar, with pump not operational (cryostat was not opened prior to this activity). After switch-on, high-vacuum threshold (10 -3 mbar) is reached in less than one hour. Pressure then starts plateauing above 10 -4 mbar. At this point, the water vapor concentration in the chamber is low enough to begin cooling down with minimal levels of condensation expected. The cryocooler is subsequently switched on at 80 W. A correspondingly faster pressure decrease rate is observed. In particular, two gradually steeper segments show, likely ascribable to different physical processes inside the chamber: e.g., decreased thermal motion and adhesion. Pressure stabilizes around ∼4 × 10 -5 mbar. Cooler power is then decreased to minimum 70 W, with a minor pressure rise occurring in correspondence. The cryocooler is then stopped. Two successive outgassing peaks are observed correspondingly. Pressure eventually settles to ∼1 × 10 -4 mbar. The CryoTelGT was one of the instruments destined to the DAMIC-M LBC, where it is currently running. Besides vacuum chain tests, further work was done on temperature control. In particular, the PID (proportional-integralderivative) control loop of the Lakeshore was set on one RTD and heater.

The cryocooler was kept at a fixed power. Whenever the sensor measured a value below the temperature setpoint, the heater would kick in and adjust its output to stabilize at the desired temperature. Tests were also performed to measure the temperature on the CCD box relative to the copper support. The setup utilized in this test is shown in Figure 5.6. UW1612S is an engineeringgrade skipper CCD that was deployed to commission the blue test chamber (see Section 5.1.3). Kapton tape was used to fix the RTD aluminum support on the CCD box. Additionally, vacuum grease was administered to perfect thermal contact. The CCD box was secured to its copper support. The CCD was not connected to the control/readout electronics during this test. The temperature on the box was found to be ∼10 K higher relative to the copper support in typical operating conditions. In general, the thermal load for the cryocooler was sufficiently low to operate the system at minimum power. Aluminum package thermal efficiency was validated at the University of Chicago with silicon CCD mock-ups.

Electronics

The DAMIC-M skipper CCD test systems feature standardized air-side electronics consisting of:

• CCD controller equipped with communication/driver/processing printed circuit boards (PCB)

• It also hosts SMA connectors to supply substrate voltage and other biases, although the latter are only used as a backup option to the bias board. The

Electronics Testing

Electronic chain components underwent individual and collective testing before CCD installation. In particular, the following tests were performed: The bias board must be supplied -30 V. Signals were measured at the boards with oscilloscope and adequate probes and verified to meet specifications. after second-stage amplification. An amplitude of 100 mV and a frequency of 1 kHz were set. The post-amplification signal was measured at the Leach video board (prior to processing) and its amplitude was found to be approximately 3.2 V.

Detector

Two 1k × 6k skipper CCDs were operated with the blue cryostat. Engineeringgrade UW1612S shown in Figure 5.6 was used to commission the chamber for operation. Science-grade UW1616S would then be deployed to assess its performance and develop CCD testing protocol (see Section 5.3). CCDs were shipped from UW, where they were packaged and tested in a preliminary manner. Figure 5.12 shows packaged UW1616S on top of its ESD-safe shipment bag and box. CCDs come from the UW with a short flex wirebonded, featuring a 50-pin D-Sub female connector on the far side. This is shorted whenever the device is not operated to minimize ESD risk. CCDs are handled on ESD-safe mats for any preliminary operation (e.g., visual inspection of the packaging). Operator sits on an ESD-safe chair and wears wrist straps connected to earth. The CCD is connected to the feedthrough vacuum side by means of a 22.8 cm Kapton flex cable with male (CCD) and female (feedthrough) 50-pin connectors. The package rests on the copper support which it can be further secured to via a threaded hole. This measure proved unnecessary: thermal contact was always good enough to reach de-sired temperatures. 3 Figure 5.13 shows UW1612S installed in the blue-cryostat test chamber during setup commissioning (plus author reflected in the far plate) and the setup with external electronics and cryostat. When no further adjustment is due, chamber door-plate is secured and vacuum is made.

The cryocooler is switched on at minimal power (70 W) when pressure is O(10 -4 mbar) to minimize condensation. Temperature setpoint is fixed between 120 K and 140 K. When the system is cryogenically stable, detector operation can begin. Electronics and detector are started up according to the following protocol:

• Leach power supply switch-on

• Bias board power supply switch-on -Supply -30 V -Assess current draw ≈ 2 mA.

• Amplifier board power supply switch-on -Supply +5 V and -5 V -Assess current draws ≈ 14 mA.

• Substrate voltage power supply switch on -Supply +45 V (usually between +30 V and 90 V).

• CCD Start Up

-Run CCDDrone's CCDDStartupAndErase executable: apply clocks and biases and perform an erase procedure. System is then left in idle mode -Assess bias current draw ≈ 40 mA.

Last step "CCD Start Up" sets the beginning of detector operations and is carried out using CCDDrone. CCD parameters are first set in the configuration file: clock amplitudes and widths, bias values and integration periods. Readout amplifier(s) and clock directions must also be specified, along with image format, number of skips and pixel binning. The erase procedure [START_REF] Bebek | 4k x 2k and 4k x 4k CCD Users Manual[END_REF] is common practice when starting up a CCD. It is performed to reduce dark current.

In fact, inactive devices get saturated with signal holes which empty surface electron traps at the silicon-insulator interface. When CCDs are first switched on, these traps are refilled with a rate increasing with temperature, releasing holes that are collected and contribute to surface dark current. The erase procedure is meant to repopulate surface electron traps quickly. In practice, the System is then left in idle mode.

substrate voltage is ramped down to 0 V, while parallel clocks are set to a strong accumulation potential (typically 10 V) over a period of few seconds, in order to flood the surface with electrons and fill the traps at once. The substrate voltage is then ramped back up to its nominal value. Typical ramp rates are 15 V/s. Figure 5.14 shows the substrate voltage evolution during an erase procedure in the blue-cryostat test chamber. After the erase procedure, system is left in idle mode: nominal clocks and bias voltages are applied and the CCD clocks charge according to directions specified in the configuration file, while selected amplifier reads out. Pixel values are not stored; no data is acquired in idle mode.

CCDDrone is used to acquire data and conduct more general detector operations. A brief review of important ones is provided:

• CCDDStartupAndErase.
Starts up Leach and performs an erase procedure. Clock, bias and substrate voltages are applied. An erase procedure is subsequently performed. Idle mode is set afterwards.

• CCDDApplyNewSettings.

Applies new operating settings according to a specified configuration file.

• CCDDExpose.

Image acquisition executable. The CCD is exposed for an arbitrary number of seconds. Parallel clocks are set to the accumulation phase (middle clock low, side clocks high). At the end of the exposure, charge is read out with the selected amplifier.

• CCDDExposeC.

Continuous readout image acquisition executable. Data is acquired continuously without setting the clocks to the accumulation phase, for an arbitrary number of seconds.

• CCDDToggleOnOff.

Switch on/off the CCD voltages in specific order. Switch-on: apply clocks, biases, and substrate voltage. Switch-off: switch off substrate voltage, biases and clocks.

These are used extensively during CCD characterization and parameter optimization activities discussed in Section 5.3. The focus is now turned to work on apparatus slow control and detector safety.

remote control of operational parameters

Slow control (SC) and data acquisition (DAQ) machines for the Low Background Chamber were commissioned with the blue cryostat. Both were made accessible via ssh for remote control. The DAQ machine runs CCD control firmware described in previous section. It features two network cards for internet connection and TCP communication with the V sub power supply. The latter allows to perform all operations related with the substrate voltage in an automated manner. The machine is equipped with 2× additional 8 TB hard drives to store locally a large amount of data. The slow control machine runs chicago _ slow _ control [START_REF] Norcini | chicago _ slow[END_REF], a modified version of the astro-slow-control package used in various astrophysics experiments [START_REF] Nikkel | Astro-slow-control[END_REF].

Slow Control

The slow control machine is a Dell OptiPlex 7080. It features an additional network management card to host the slow control internal private network.

The SC system was set up in collaboration with the DAMIC-M group at the University of Chicago. Astro-slow-control is based on C backend and php frontend and employs MySQL for databasing. For each instrument there is a C process populating a master MySQL database. Further processes are available providing additional capabilities, e.g., alarms. All monitoring and control of experimental telemetry is done using the php web interface. This features numerous functionalities: plotting, low-level analysis, logging, etc. An example of slow control plot was shown in Figure 5.5. Figure 5.15 illustrates the package features. A private internal network is set up to monitor and control instruments. The communication between these and the host machine is established using different physical ports (ethernet and serial) and protocols (TCP/IP, modbus and serial). Ethernet is preferred, since the network is constructed using a multiport ethernet switch. Serial device servers (serial to TCP converters) are used whenever instruments do not have ethernet/TCP capabilities.

All instruments requiring remote monitoring and control were included in the SC private network. In the case of the vacuum pump, a serial to ethernet conversion was not implemented and communication was established using serial protocols. Figure 5.16 shows the slow control private network along with other devices of the blue cryostat external electronics. Instrumentation not mentioned so far played an important role in the system: the APC SMC1000 uninterrupted power supply (UPS) and the Raritan PX2 power distribution unit (PDU). The former is essentially a battery taking over power supply to critical instrumentation in case of power outage. This will be fur- ther discussed in terms of detector safety in Section 5.2.2. The PDU is used for hardware switching. In this test system, it controls only pump status.

Alarms are the most important SC safety capability. Lower and upper thresholds are set for many of the monitored parameters. Whenever these are exceeded, visual and acoustic warnings are issued in the web interface and on-call users are notified via email and SMS. Figure 5.17 shows an example of alarm management on the SC interface. When reject temperature exceeds 50 • C for an interval longer than the grace period, an alarm is issued.

Detector Safety

Events representing a safety hazard for CCD detectors must be promptly counteracted. The main danger is condensation, which could produce shorts and thus damage to electrical parts. Condensation depends on both pressure and temperature. However, pressure is intrinsically more critical, also due to the time-scales of pressurization as opposed to warm-up (∼h versus ∼d). It is therefore crucial to maintain high vacuum in CCD test chambers. As a rule of thumb, DAMIC-M CCDs are operated at pressure < 10 -4 mbar. Ambient temperature operation is possible for commissioning purposes. In such case the substrate voltage is set to 0 V to limit charge collection, due to high leakage current. The two main safety events are power outage and pump failure.

In a power outage, all parts in the system will undergo a hard shut down, including the vacuum pump. The uninterrupted power supply was installed as a safety countermeasure. Only pump and cryogenic controllers were plugged on the UPS (see Figure 5.16), in order to maximize on-battery runtime. This would be few tens of minutes. However, power cuts this long are very rare: none occurred at LPNHE during chamber operations.

In case of pump failure, detectors must be promptly shutdown, since the risk of short is immediate. A safety watchdog daemon was integrated to

CCDDrone to this end. This periodically queries the slow control database for cryostat pressure and pump rotation speed values. CCDDToggleOnOff executes shutdown if any one of these quantities is beyond user-defined threshold for more than two consecutive measurements (occurring every 5 s). Additionally, system managers are notified via email. This mechanism proved effective and safely shut detector down during two pump failures witnessed during blue cryostat activities. CCD performance was found to be unaffected at operation resumption. Note that it is actually desirable to shut down all power supplies and Leach controller in case of pump failure. This requires a more sophisticate control system. DAMIC-M will deploy a DCS safety system under development at the University of Zürich (UZH), complementary to the slow control. The DCS will be able to perform the actions that put detectors in the safest state. First tests of a prototype of the DCS were carried out with the blue-cryostat test chamber, for operation at the LBC. Tests demonstrated successful integration with the slow control.

skipper ccd testing

Both orange and blue cryostats were used to test skipper CCDs. These systems have similar features from a cryogenic standpoint: descriptions provided so far are representative of the former as well. CCD performance studies described in this section were conducted with the orange test chamber during blue cryostat commissioning.

During CCD operations, the video output signal was monitored with an

Acquisition Strategy

Data acquisition was performed using CCDDrone. The erase procedure performed at start up produces undesired patterns of charge which normally fade after few minutes. Performance studies can then begin. Data was acquired in different formats, both in single-skip and multiskip mode. Single-

Analysis Software

Custom software was built in python for reconstruction and analysis of skipper images. The CCDTesting modular framework [START_REF] Traina | CCDTesting[END_REF] comprises libraries and executables dedicated to distinct analysis scopes. A json configuration file is filled in with specifications on the CCD under test (e.g., CCD format), desired analysis options (e.g., row and column range) and information to report on (e.g., noise plots). Selected information is reported into a L A T E X pdf document on a per image basis. Multiple images can be analyzed automatically making use of available shell scripts. The framework was initially conceived for parameter optimization; it would later be extended for further characterization tasks: charge transfer, data quality, response linearity and cluster reconstruction. These will not be discussed further. The optimization code executes the following tasks:

σ ro = σ 0e -/k e ,
where k e is the ADU per electron calibration constant.

Parallel and serial CTI can be initially checked for simply by looking at CCD images. In case of significant CTI, evident vertical and/or horizontal patterns appear in proximity of clusters. CTI between skips is also possible.

The signature of skip CTI is the difference in same-pixel charge across skips.

First-second and second-last skip difference are of particular interest. In case of bad parameters most charge will typically be lost between first and second skips. However, if the effect is only modest (e.g. 10 -3 per skip), the cumulative CTI over several hundreds of skips should be looked at through particular, the following quantity -the CTI coefficient -and its uncertainty are computed:

k CL = N > -N < N > + N < (5.1)
where N > and N < represent the number of entries above 3σ and below -3σ, respectively. The coefficient is expected to be 0 (within uncertainties) in absence of CTI, and approach ±1 when it dominates. Its uncertainty u(k CL ) is extracted using error propagation, assuming N > and N < to be binomially distributed according to probabilities measured with the PVDD. The ratio The levels of dark current in a CCD must be assessed to establish detector grade. As is customary, CCD images should first be inspected for hot regions.

S k = k CL /u(k CL ) is
An example where defects were judged compromising was seen in Chapter 4, for the first DAMIC-M pre-production batch. If only few hot columns and pixels are found, they can be rejected using masks. A CCD is considered science-grade if dark current does not exceed the 10 -3 e -/pixel/d scale.

In CCDTesting, two algorithms are available to measure dark current. The first simple algorithm developed is named anticlustering (AC), since it looks for charged pixels surrounded by an empty crown. The knowledge of the ADU-charge calibration constant is required to perform anticlustering. This is obtained as the distance between centroids of contiguous single-electron peaks. The average image is calibrated, expressing pixel values in electron units. Anticlustering provides a lower estimate on dark current since it counts the number of isolated one-electron pixels within 2σ from the centroid. The dark current rate in e -/pixel is computed as:

λ AC = N iso 1e -(2σ) N iso 0e -(2σ) (5.2)
Such approximation is acceptable because the ne -peak amplitude is suppressed as the nth power of the actual rate, λ. 5 The denominator of Equation 5.2 is given by the number of isolated pixels with value within 0 ± 2σ e - (i.e., empty). This choice is justified as follows. Numerator and denominator have roughly the same selection (in)efficiencies since cases where one or more nonzero-electron pixels fall in the surrounding crown are not counted.

In particular, the following relation holds:

N contig 1e - N iso 1e - numerator ≈ N iso 1e -
N iso empty denominator (5.3) where N contig 1e -is the number of pixels with 1e -whose crown contains another one-electron pixel. Note that one-electron pixels are doubly counted out in this approach. This entails a subdominant O(λ 2 ) correction to λ AC . The definition of λ AC was further checked with a toy Monte Carlo study, applying the AC algorithm on dark-current only simulated datasets. Note that anticlustering inherently discards most pixels belonging to events that are not point-like. Whenever single electrons are not fully resolved, peak overlap degrades the quality of λ AC as a dark current estimate. There is nonetheless

CCD Performance Studies

The DAQ and analysis strategies presented thus far have been employed to optimize CCD performance. Systematic studies were conducted with sciencegrade skipper CCD UW1603S6 using the orange cryostat. The chief activity were parameter scans through working configurations, in view of CCD testing for DAMIC-M production. This was a cross-institutional effort, with similar activities taking place in other groups. Parameters ought to be in specific relationships with one another for efficient charge collection, transfer and readout.

Parameters relevant for charge collection are V sub , ensuring full depletion, and clocks, which set the potential minimum in the conductive p-channel. Thick buried channel CCDs are fully depleted at 40 V substrate voltage and can be applied up to 200 V [START_REF] Holland | Fabrication of back-illuminated, fully depleted charge-coupled devices[END_REF]. The Leach ARC-32 board can deliver clocks in the [-13 V, +13 V] range. Arbitrary values can be used for both low and high rails, as long as V lo < V hi and differ enough to create a potential well of sufficient charge capacity. Transfer efficiency across rows and columns entirely depends on parallel and serial clock rails and time widths. Few volts (difference) and 10 µs widths typically suffice to maintain nominal high CTE. The readout stage consists of a transfer part across summing well, output gate, sense node and dump gate, and a charge sensing part using readout and reset transistors.

The following parameter relationships must be fulfilled:

• SW hi > OG hi > V R (charge to sense node) • SW lo < OG lo < V R (charge to summing well) • RG hi > V R -V eff (close reset switch) • V DD > V R (readout gain) • V drain < DG lo < V R < DG hi (measure/dump charge).
where V eff is the difference between the applied gate potential and its value in the buried channel. Timings (pulse widths and integration) must also be set appropriately. In general, given the interconnectedness of CCD operating parameters, optimization proceeds empirically with guidance from above relationships.

Work with 1603 was conducted with to gain expertise in CCD testing. Performance at nominal parameter values was science-grade, and was generally maintained whenever listed relationships were fulfilled. Noise and dark current were the main quantities of interest for optimization. Charge transfer efficiency (parallel and serial) was not studied in depth: the general approach was to assume nominal performance unless evident patterns were observed (they were not). Skip CTI was more closely monitored since readout stage parameters were systematically studied. Readout noise strongly depends on integration time and readout transistor drain voltage V DD (not to be confused with V drain , to dump charge after readout). Amplifier gain is an increasing function of both (of V DD -V R in the latter case). Optimization must keep this into account.

A parameter scan was performed to study noise as a function of t int and V DD . The SIPC DAQ strategy was used. Nominal values were 10 µs and -17 V, respectively. The integration time scan was done across the [5 µs, 30 µs] range, with a step of 5 µs. CCDTesting was used for data analysis. Figure 5.25 shows gain and noise as functions of the integration time. Gain increases linearly with integration, as expected. Calibrated noise (solid red line), rather high for t int = 5 µs, stabilizes around an optimal σ avg ≈ 0.14 e -(average image case) at 10 µs. 7 These results are consistent with studies conducted in [START_REF] Matalon | Searching for Light Dark Matter with DAMIC at SNO-LAB and DAMIC-M : investigations into Radioactive Backgrounds and Silicon Charge-Coupled Devices[END_REF]. Given similar noise for t int between 10 µs and 30 µs, a priori any integration time could be chosen. The nominal t int = 10 µs is justified because readout time increases linearly with the integration period, which takes up most of the duration of a single NDCM.

following skips because of a transient from horizontal clocks. This can be seen by noting that 0.15 • √ 1000 e -< 6e -, and that the single-skip noise trend does is less stable than the multiskip one. showed a gradual noise rise for V DD < -17 V. Increasing contributions from thermal noise and amplifier IR light are thought to be responsible for such behaviour. V DD was set to -16 V, with a single skip noise of about 5 e -. Another noise scan study was conducted tweaking reference voltage and other readout stage parameters (V DD , SW, OG and DG) together in order to preserve correct relationships and amplifier gain. Functionality of the reset switch was always ensured since V R was lowered in this study. A step of 0.5 V was used for a range of 3 V. While noise remained stable across the scan, an interesting effect attributable to charge injection from the drain was remarked. In particular, the last image was acquired (unintentionally) with SW lo + V eff < V drain .

A sudden jump in dark current was observed in correspondence. Another image was taken with same parameters except for V drain , which was reduced by 1 V. Average image pixel value distributions are compared in Figure 5.26.

Further lowering V drain brings charge back to nominal levels, thus supporting the drain injection hypothesis.

posure, these represent a dark current about two orders of magnitude higher than SNOLAB. However, the comparison is not straightforward in that environmental sources of few-electron events play a much more important role at shallow sites where radiopurity is not controlled.

CCD testing activities were conducted with the blue cryostat as well. These tests focused on evaluating performance of CCDs UW1612S and UW1616S, reproducing UW results. In both cases, compatibility was found. Since testing methodology and machinery were amply discussed, these simpler tests are glossed over. Suffice it to say that relevant performance features listed in Chapter 4 were evaluated to assess detector grade. As of now, engineeringgrade 1612 is used for DAMIC-M electronics testing, which is the main activity ongoing at LPNHE. Science-grade 1603 and 1616 will be re-deployed for precision studies with said electronics once it is in a preliminary final state.

CCD Testing Protocol

The CCD testing protocol defined following extensive cross-institution activities consists of these steps:

1. Visual inspection of packaged CCD: amplifier status, wire bonds integrity, presence of dust/dirt, orientation mark, flex status.

2.

Amplifier check: single-skip image for each amplifier. Assess charge/tracks, noise, defects.

Skipper calibration check.

• Skip CTI: 10-skip, 6200 × 10 image, 10 s exposure, no clear. Two configuration files.

• Calibration: 1000-skip, 1550 × 20, 1 × 4-binned post-clear image.

Measure noise trend and dark current. Two configuration files.

A report is produced for each CCD. Two different configuration files are used for steps 2. and 3. In fact, work across institutions showed that the majority of devices perform well under these settings. Additional tweaking of crucial parameters according to reported relationships is envisioned in case of need.

The goal within DAMIC-M is to use few common configurations for its ∼200 devices. Same-module CCDs will operate under the same settings. The protocol was designed to efficiently test up to 8 CCDs per week, using a test chamber with a 4-CCD capacity at the University of Chicago. First pre-production batch of Chapter 4 was characterized using this protocol.

T H E D A M I C -M L O W B A C K G R O U N D C H A M B E R

The

lbc apparatus

The LBC is hosted in the clean room where DAMIC-M will be constructed. A commercial humidifier is used with ultra-pure water to maintain necessary humidity levels (> 35 %) during CCD packaging. Finally, a movable hydraulic crane is kept inside the detector room in order to move heavy polyethylene parts and lift the top part of the LBC cryostat.

This was built by ADS

All materials were thoroughly cleaned before accessing the detector room.

In particular, instrumentation commissioned at LPNHE was cleaned inside the (LPNHE) clean room using lint-free wipes and IPA, after flushing grooves and cavities with dry nitrogen to remove any debris. Composite instruments (e.g., cryocooler) and machines were partially disassembled for the purpose.

All items were then triple-bagged using polyethylene bags and an impulse followed using a 1 : 99 citric acid (HOC(CO 2 H)(CH 2 CO 2 H) 2 ) and >18 MΩ water solution. Parts were submerged into the solution, which was stirred for about 10 minutes. Passivation is meant to protect copper from oxidation. Parts were then rinsed, dried, and triple-bagged for shipment. All described procedures were designed with PNNL staff with expertise on material cleaning for low-background applications [START_REF] Hoppe | Cleaning and passivation of copper surfaces to remove surface radioactivity and prevent oxide formation[END_REF][START_REF] Hoppe | A method for removing surface contamination on ultra-pure copper spectrometer components[END_REF][182].

Apparatus Construction

LBC shielding and cryogenics were set up in two successive work campaigns.

Support structure and external shielding were assembled first. Cryostat, internal shielding and cryogenics were installed subsequently.

Support Structure and External Shielding

The support structure was designed at IJCLab and essentially consists of an aluminum frame equipped with stainless steel rails and a rack-and-pinion linear actuator conceived to open and close the LBC external shielding with the aid of a lever. The structure is meant to accommodate and support more than 2000 kilograms of lead and polyethylene (PE), as well as cryogenic equipment such as pump and cryocooler. Its design was informed by performing mechanical simulations. Further information will be included in the LBC technical paper under preparation [START_REF]The DAMIC-M Low Background Chamber[END_REF]. opening mechanism has been reviewed over the last few months and will be upgraded in the next work session at LSM.

Cryogenics and Internal Shielding

The Low Background Chamber OFHC copper cryostat was manufactured at CINEL, Italy [184]. Soon after fabrication, in November 2020, it was shipped and stored at LSM to minimize cosmic activation. The cryostat has a two-fold structure. Its upper part hosts CCD box, amplifier PCBs and internal shielding. The lower part is devoted to cryogenics and vacuum-side electronics, with five openings for flanges carrying ports and feedthroughs. Figure 6.5

shows the LBC cryostat at the end of manufacturing. The cryostat was annealed during fabrication, making the copper softer. Careful handling was thus required. A visual inspection was conducted after reception at LSM, in a cleanroom environment. All dimensions were checked with mm precision, in particular flange diameters and vertical sizes at multiple locations to ensure parallelism. All joints and flange sealing surfaces were inspected for bumps/warpings. No significant damage was spotted. OFHC cold copper parts and CCD box were machined at the University of Zürich. Cryogenics was installed in about a week. Notable supplies needed in the process were: Kapton tape, loctite, vacuum grease, high-vacuum aluminum foil and thermal epoxy. The cryostat was displaced by means of the hydraulic crane. Thermal chain and cryostat bottom were installed first. Figure 6.6 shows some of the The other pair is intended as spare. A cylindrical copper arm is mounted on the table top, transitioning to the top part of the chamber. At this stage, the cold assembly is mounted into the cryostat, which subsequently can be fit LBC vacuum performance proved excellent since inception, with pressures O(10 -6 ) and O(10 -7 ) mbar at cryostat and pump, respectively. In few occasions, pump did not reach nominal 90000 rpm. It was generally not necessary to open the chamber to diagnose and correct low vacuum performance: loose flanges, joints or clamps would be culprits. Desired thermal performance was achieved more effortfully because of poor thermal contact at the cold headcopper strap connection. This was found to be a side-effect of the electrically insulating arrangement. Various configurations preserving insulation were attempted. Eventually, the Kapton patch and plastic washer mentioned previously were used. The final arrangement granted good thermal performance, with cold copper finger temperatures ∼100 K at 150 W cooler output power with one operating CCD. Thermal chain was definitively validated by confirming that desired temperatures could be achieved on the CCD box. Note that the LBC thermal load is much larger than the blue cryostat test system, thus higher cooling power is needed to achieve similar temperatures.

Electronics and Detector

LBC electronics was tested at LPNHE and UW before shipment to LSM. It was then validated on site, in a similar manner as with the blue cryostat test system. Analogous equipment was used for such tests (oscilloscope, probes, ESDsafe tools, etc.). Salient differences between the two setups electronic chains are vacuum-side two-to-one and amplifier boards in the LBC. The same CCD controller (the Leach) is nevertheless used. This will eventually be replaced by DAMIC-M electronics for underground testing with science-grade CCDs.

A simplified schematics summarizing the LBC electronics chain for one CCD is shown in Figure 6 tions were adopted to carry out the transfer. Humidity in the detector room was increased to ∼40% using a commercial humidifier with ultra-pure water.

Slow Control, DAQ and Safety

The Low Background Chamber was provided with full remote control capabilities. The slow control framework described in Section 5. As a result, it can be interfaced more easily with other systems such as the slow control, for e.g. keeping track of the cryogenic conditions during data taking. Additionally, the DAQ acts as a wrapper to provide users with a consistent acquisition scheme independent of the controller in use. More details will be found on the LBC technical paper under preparation [START_REF]The DAMIC-M Low Background Chamber[END_REF]. The LBC instrumentation network is shown in Figure 6.13. The only instrument yet to be included in the network is the RAD7 radon monitor [187], so far used for occasional measurements (5 -20 Bq/m 3 ). As the schematics shows, two UPS supplies are used to ensure uninterrupted power to LBC instrumentation. The one with larger capacity is provided by LSM; the other, a commercial APC 2200, is where most instruments are physically connected. This combination can provide instruments with continued supply for over 1 hour, in case of long power outage. The 48 V cryocooler power supply is connected directly to the LSM UPS. This choice was made to prolong runtime, considering relatively long thermal timescales. In the unlikely scenario of an outage longer than the cumulative runtime, instruments would undergo a hard shut down.

While this is not ideal, condensation would happen 1 h afterwards and detectors would be safe. If electricity supply is restored with condensation in the system, CCD controller and supplies will switch back on, but provide no output voltage. The system is protected against pump failure using the same slow control-DAQ integrated system described in Section 5.2.2. However, only pump rotation speed is monitored, since pressure gauges stay switched off to prevent IR production. The UZH DCS system will soon be installed to provide a more robust hardware-only safety shutdown mechanism.

science-grade ccd characterization

The first installation campaign at LSM ended mid-December 2021. The Low Background Chamber was set up for operation with CCD 6415. As mentioned earlier, CCD 6414 had been installed as well, but remained powered down un- This section discusses the characterization work conducted on noise and dark current with the LBC charge-coupled devices. Subjects are treated separately, following a chronological order and highlighting the differences introduced by parallel operation of two CCDs and shielding installation. Whenever no distinction is made between same-CCD amplifiers, statements can be assumed to hold in general. Note that the goal of these studies was understanding detectors in view of the hidden sector dark matter analysis. Accurate quantification of some effects was unneeded insofar as they can be selected out or neglected. For example, non-negligible CTI can be dealt with appropriate masking of images.

Electronic Noise

UW6417D first measured rather high electronic noise ( 10 e -). Similar results were later obtained with science-grade devices. These values are in contrast with the ∼5 e -expectation from the Leach, which motivated further adjustments in the LBC setup.

Noise Suppression with 6415

The guiding principle for noise suppression was identifying and isolating possible sources thereof. Initial efforts concentrated on electrical insulation of notoriously high-noise devices (e.g., cryocooler). This was one of the LBC design criteria, but unintended connections could have been made accidentally during installation. Further potential sources were checked subsequently. Remarkably, the dominant contribution was found to come through the oscilloscope ( 10 e -). However, the device itself did not generate the noise, nor was this produced by signal distortion (e.g. from an impedance mismatch). the contribution was ascribed to a ground loop. In fact, the Modane underground laboratory is not connected to a "clean" ground line. Instead, a big metal structure overarching the laboratory platform serves the purpose. All experiments and utilities use this ground, and, in particular, DAMIC-M clean room floor and walls are connected to it. Electrical transients propagating across are thus likely responsible for the observed noise. Suppressing the connection would bring electronic noise to more reasonable levels of ∼10 e -. In general, a way to potentially mitigate noise from ground loops is coupling conductively different parts of the setup to bring them to a common potential.

This can reduce undesired currents seeping in the readout chain. The efficacy of such measure depends on specific loop and parts involved. One strategy that proved fruitful in test chambers is grounding the CCD box or connected elements to the cryostat. This approach was attempted at the LBC as well:

cold mass table was grounded to chamber and two-to-one boards as shown in Figure 6.17. These adjustments along with parameter tweaking improved resolution to single-skip values of about 7 e -. Interestingly, the single-skip expectation extrapolated as σ ro = σ avg • N skips is ∼4.5 e -. This means that noise responsible for the discrepancy is (partly) averaged out. LBC data is acquired using synchronously the L and U skipper amplifiers of serial register 2

(SR 1 has conventional amplifiers). This effect is observed for both. As a consequence, the contribution must be external to either readout circuit. Given above considerations, its origin is likely ground loops. Other examples will be Figure 6.17: LBC grounding connections. The cold mass table is grounded to chamber (left) and two-to-one board (right).

seen in the context of the installation of the second DAQ. These perturbations affect negatively the LBC science reach (see Chapter 7). It is thus important to design ad hoc solutions in view of DAMIC-M.

Second DAQ Commissioning

The installation of a second data acquisition system (DAQ2) was expected to increase electronic noise. On the one hand, electrical connections introduce ground loops and pick-up. This contribution was expected to be secondary, however. More delicate was the question of operating two CCDs with independent, unsynchronized controllers. One CCD clocks and readout pulses are potential noise sources for the other. These effects can significantly affect performance; one example will be discussed shortly. Before installation of DAQ2, few test images were acquired with CCD 6414 using DAQ1 (i.e., the one used with 6415 until then), demonstrating good performance. DAQ2

could thus be installed. The additional Leach controller was hooked up to the power distribution unit along with the first. All power supplies were connected to the DAMIC-M UPS. Upon completion of the electronic chain, first data was acquired with 6414 and DAQ2. Figure 6.18 shows the noise spectra from multiskip images acquired with DAQ1-6414 (DAQ1 installed only) and DAQ2-6414 (both installed) combinations. In the latter case, DAQ1 and 6415 were connected but powered down. The installation of DAQ2 introduces highfrequency noise components well evident in the corresponding spectrum (red curve). Importantly, both Leach controllers were evaluated (at the LBC) and found to have similar noise components. The one prominent difference consists in the two peaked structures appearing slightly below and above 5 kHz.

These come from second and first Leach, respectively. Single-skip noise values of ∼12 e -were measured for both 6414 amplifiers. Sub-electron resolution was achieved. Expectations from average image resolution were ∼6 e -. This noise component is thus partially averaged out and can be coped with.

Focus subsequently shifted to operating the two detectors conjointly, the main concern being cross-talk. CCDs 6414 and 6415 were switched on in parallel on March 22nd. Noise levels rose correspondingly by few electrons. Both detectors maintained nonetheless single electron resolution and overall good performance. Tests were carried out to validate two-DAQ operations. In particular, it was checked that overlapping readouts do not compromise data quality. This was typically the case, although parameter combinations were encountered which would significantly worsen performance. An interesting example is the summing well width. Setting same values for both CCDs (parameter set for both amplifiers at once), would introduce important pedestal fluctuations across the image. This effect was observed for two values: 0.48 µs and 0.8 µs. While it can be corrected for by row-wise pedestal subtraction, data quality is ultimately degraded. The noise components discussed so far affect CCDs in a correlated manner. This is seen in the mirror pixel value map shown in Figure 6.20. Sciencegrade performance is conserved, since this noise is partly averaged out. However, data quality is degraded, which must be dealt with at an analysis level.

Correlated noise subtraction algorithms for skipper devices are under study.

These can potentially suppress above contributions to negligible levels. Also note that DAMIC-M electronics will operate CCDs synchronously. This is expected to solve above issues with parallel operation. Noise and gain values for current LBC operations are reported in Table 6

Dark Current

Dark current measurements conducted with 6415 in early 2022 were characterized by ∼30× higher backgrounds due to the absence of external shielding. Measurement precision is particularly affected by background events producing few-electron signals. Additionally, prominent CTI started originating around high-energy clusters during temperature cycling. Charge from loss trails mimics dark current and bias measurements. These issues were sorted out by the time second DAQ and shielding were installed. Higher precision was possible thereafter. In general, a high dark count rate was measured relative to ∼10 -4 e -/pixel/d DAMIC at SNOLAB levels. This was ultimately ascribed to the CCDs themselves (i.e. to dark current). Impurity concentration and structural defects at the source of dark current are generally correlated with CCD manufacturing. Note that few-electron events are the main background affecting hidden sector searches with CCDs. It is thus crucial to reduce dark current and other sources thereof to achieve higher sensitivity.

Dark Current Suppression with 6415

First measurements with 6415 highlighted a prominent contribution from the serial register. The control sequence was thus modified to sweep out and dump any charge thereby produced, prior to each parallel transfer. Subsequent acquisitions were carried out in SIPC mode and showed a clear-cut exposure dependence, apparent in Figure 6 The first LBC data run started on February 9th and was carried out under optimized settings for hidden sector sensitivity. Image format was set to 640 × 840 650-skip images with 10 × 1 binning. Both L and U serial register 2 amplifiers were used to acquire images in continuous readout mode. The latter maximizes exposure, as no data is thrown away and there is relatively few dead times. This is not the case for the SIPC, which, however, can be leveraged to reduce the rate of few-electron events (see Chapter 7). One physical CCD would be read out in under five images in this approach, with dark current reaching steady state during the fifth. A ×10 serial binning was favored for faster readout. In this configuration, it would take about 6.5 hours for the system to become stationary, to contrast with ∼3 days if the physical CCD were read out pixel by pixel. Note that binning could be implemented by virtue of CIC subdominance. The number of skips was chosen as a compromise between readout time and resolution. In fact, shorter readout times give inherently smaller few-electron rates per unit exposure, which is what drives hidden sector sensitivity. This is due to concurring Poisson power law and linear dependence on exposure. However, less skips must be performed to reduce readout time, which degrades resolution and boosts spurious counting from lower-charge pixels (0, 1 and 2e -). If dark current dominates, it can be shown that there is an optimal point of operation if e.g. the number of >2e - events is to be minimized. The following relation holds:

N >2e -= N DC >2e -+ N spurious >2e - (6.1)
where: cence could not be reduced by tweaking readout amplifier parameters. Its cause was eventually found to be in the summing well rails for both CCDs.

N DC >2e -≈ N DC 3e -= N pixels × P(3e -|λ). (6.2) N spurious >2e - ≈ N 0e -× P G (q 2.5|µ = 0, σ avg )+ N DC 1e -× P G (q 2.5|µ = 1, σ avg )+ N DC 2e -× P G (q 2.5|µ = 2, σ avg ) (6.3)
Changing SW rails from (-3 V, 5 V) to ogy due to serial binning. Prominent parallel and serial CTI is also visible.

(-9 V, - 2
No clusters are observed in run 2 image, as a result of shielding installation.

Incidentally, charge transfer efficiency highly improved in the second period of operations. The amelioration was arguably caused by slower temperature cycling, with a set ramp rate of 0.1 K/min (as opposed to initial 1 K/min). CTI was observed to be negligible and, given scope of first data runs, an accurate quantification was unneeded.

A novel dark current reduction approach found effective by the RADAC

D A R K M AT T E R S E A R C H E S W I T H T H E L B C

The analysis of the first LBC science data is ongoing to constrain sub-GeV hidden sector dark matter interactions with silicon atomic electrons. A partial background model is used to exclude potential signals in yet unexplored regions of the mass-cross section parameter space. The first two commissioning data runs conducted with one and both detectors, respectively, were exploited to develop analysis methodology and data quality cuts. The latter are only briefly discussed in this chapter. Third and ongoing fourth science runs are used to set 90% confidence level limits on the dark matter-electron scattering cross section. This chapter focuses on the construction of the inference framework and the results of the latter analysis.

analysis framework

Author and J.P. Zopounidis constructed DamicMSignal inference framework to estimate LBC sensitivity to hidden sector dark matter and extract exclusion limits [START_REF] Traina | DamicMSignal -Currently private on GitHub[END_REF]. The framework is built in Python and features six classes to execute the following steps: computation of physical signal and background, application of detector response and sensitivity forecast/limit-setting using likelihood ratio testing. Relevant parameters such as galactic halo model, detector operation settings and dark matter mediator, mass and cross section are reported in a configuration file. Data is fed into the framework in the form of a calibrated cumulative pixel charge distribution, stemming from the hundreds of images acquired in a data run. This approach permits modeling of signals as low as ∼1 eV, which makes the search sensitive to hidden sector candidates with masses down to few hundreds of keV's. Masks are produced (outside the framework) to veto clusters, hot regions and charge transfer inefficiency.

The limit-setting strategy entails fitting a background-plus-signal model to the cumulative PCD. The background model is simplistically assumed to be a Gauss-Poisson convolution, as expected from dark current and white readout noise. This represents a valid approximation when other sources of dark counts are subdominant. The dark matter-electron scattering rates are computed using the QEDark code [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF], which makes use of density functional theory to describe the collective dynamics of electrons in a crystal lattice.

Physical Signal

The expression used in QEDark to compute the physical signal rates is:

dR crys d ln E e = ρ χ m χ N cell σe α m 2 e µ 2 eχ d ln q E e q η(v min (q, E e )) F 2 DM (q)|f crys (q, E e )| 2 (7.1)
where ρ χ is the local dark matter density, N cell = m target /m cell is the number of unit cells the crystal target is subdivided into (2 lattice atoms form a cell), σe parameterizes the interaction strength (σ e is used interchangeably in the following), α is the fine structure constant, η represents the inverse mean speed of DM particles with respect to a terrestrial observer, F DM is the dark matter form factor encoding momentum dependence of the interaction, and the crystal form factor f crys encodes the transitions of atomic electrons. The dark matter form factor reads: F DM = αm e /q n . The case n = 0 describes point like interactions via heavy mediators, the case n = 1 electric dipole coupling, and the case n = 2 interactions via ultra-light (or massless) mediators. The halo dark matter velocity distribution is approximated to be spherically symmetric to get to above expression. The computation of the inverse mean speed η is done according to equations B.4 and B.5 of [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. Halo parameters recommended in [START_REF] Baxter | Recommended conventions for reporting results from direct dark matter searches[END_REF] are used in DamicMSignal for such computation. These are reported in Table 7.1 along with the local dark matter density value utilized.

ρ χ v 0 v esc v E (GeV/c 2 /

Detector Response

Physical events are converted in detector signals taking into account silicon physics and detector effects. An energetic dark matter particle depositing an energy E in the CCD will produce a mean number of electron-hole pairs:

N = E ε eh (7.
2)

The first step carried out in translating physical events to detector signals is thus energy-charge conversion. Instead of using Equation 7.2, the Monte Carlo approach exploiting pair creation probabilities P n (E) provided in [START_REF] Ramanathan | Ionization yield in silicon for eVscale electron-recoil processes[END_REF] is used. In fact, in the low-ionization regime (E 20 eV), usage of ε eh can introduce systematics up to 50%, since actual bandgap extent and concurring processes such as phonon emission are neglected. Figure 7.2 shows the charge differential rates from heavy mediator 10 MeV dark matter interaction, produced using Equation 7.2 (teal) and results from [START_REF] Ramanathan | Ionization yield in silicon for eVscale electron-recoil processes[END_REF] (red), respectively. Significant differences can be observed across the entire charge range. Note that P n (E) values in use have been extracted for a temperature of 100 K. However, difference relative to ∼120 K of LBC CCDs is demonstrably negligible [START_REF] Ramanathan | Ionization yield in silicon for eVscale electron-recoil processes[END_REF].

Charge simulated in this fashion is injected at a specific position in a 3072 × 4128 pixels area corresponding to a single amplifier, assuming a 15 µm × ities provided in [START_REF] Ramanathan | Ionization yield in silicon for eVscale electron-recoil processes[END_REF] (dividing simulated energy deposition value by 3.75 eV mean electron-hole ionization potential).

15 µm pixel size and a sensitive thickness of 669 µm. Injection coordinates are simulated uniformly according to these dimensions for each event. Note that the low-energy depositions relevant in this analysis can be considered pointlike to a good approximation, since electron inelastic mean free path in silicon lattice is ∼1 -10 nm, orders of magnitude smaller than pixel size. A model calibrated on muon surface data acquired at UW with LBC-like 6k × 4k CCDs is used to simulate charge lateral diffusion: in a single bin. However, clusters across the edge of binning segments are distributed over different bins, which leads to the systematic difference between red and black histograms. The number of expected events from a kg-year exposure is simulated in 3000 images. This convention is assumed in the rest of the detector response section. Empty pixel entries are not reported since they do not provide important information on the detector response. Binning boosts signal to background ratio and is thus investigated to maximize sensitivity (see Section 7.2). This happens when diffused signal charge is gathered back into one single binned pixel, with no correspondin increase in dark current (since readout is faster, but charge from several pixels is cumulated into one). Binning should thus be performed at a hardware level, and not post acquisition, since in the latter case dark current charge will be cumulated too. The effect of hardware and software binning on the pixel charge distribution is seen in Figure 7.4.

                   A =
Read out noise is modeled as well as a source of background. Figure 7.5

shows the noise-injected pixel charge distribution. Vertical axis units differ for the two histograms, with a post-noise distribution bin width of 0.01 electrons.

As will be presented in next section, dark current and noise are not simu- where the numpy np.geomspace(a,b,n) function returns n uniformly spaced points in log space with endpoints a and b. For each mass, a benchmark cross section is selected such that a number of events 150000 ± 1000 is produced in a kg-year exposure to maintain sufficient statistics while keeping the overall (for all models) simulation time shorter than few hours. The kg-year signal model events are simulated in 3000 3072 × 4128 pixel images. Events per image are produced according to a Poisson rate equal to 150000/3000 = 50. A dedicated study was carried out to demonstrate event pile-up negligible for these settings. The pile-up probability for these simulations is estimated to be <1% (binning included). Signal PCDs are transformed into pixel charge probability mass functions normalized to unity, for the corresponding benchmark cross section. A critical difference introduced by a variation in exposure or cross-section concerns the 0-e -probability. Higher charge bins preserve their mutual relationship, since increasing the number of events on average increases their content by a constant factor. The 0-e -probability is computed as the complementary term for the sum of probabilities to add up to unity.

This operation encodes the fact that higher cross sections lead to higher pixel population over the same exposure period. In order to compute probability mass functions for cross sections different than the benchmark value, nonempty bin contents are scaled down with a multiplicative factor. The zeroelectron bin is adjusted correspondingly, preserving normalization. The simulation pipeline was validated for parameters relevant for the analysis scope and double-checked with an independent framework built by DAMIC-M collaborators at the University of Chicago.

Inference

The DamicMSignal inference framework makes use of the profile likelihood ratio test statistic. Procedures detailed in [START_REF] Cowan | Asymptotic formulae for likelihood-based tests of new physics[END_REF] are used to estimate the LBC sensitivity and set limits on heavy and ultra-light mediator dark matter-electron scattering cross sections. 1 Signal models for such candidates are constructed as explained in previous section, with the signal strength (i.e., the cross section) as free parameter (masses are scanned across to set upper limits). The background model is fully characterized by a Poisson dark current rate and a Gaussian white readout noise. These two quantities are left as free parameters in the likelihood fit. The pixel charge distribution model used in the likelihood analysis is given by Equation 7.4:

Π(p) = N pixels +∞ n q =0 n q j=0
S(j|m χ , σ e ) × P(n q -j|λ)G(p|n q , σ avg ) (7.4) where n q is the number of charges in a pixel, S(j|m χ , σ e ) is the probability of a signal contribution of j electrons to a given pixel with n q charges, and the Gauss-Poisson convolution factor is the background model n q -j pixel charge contribution. The model describes the pixel value as a convolution of signal and background. Setting σ e = 0 gives the background-only model and Equation 7.5 is true by construction:

Π bkg (p) = N pixels +∞ n q =0
P(n q |λ)G(p|n q , σ avg ) (7.5)

The likelihood fit to data is performed by minimizing the negative binned log-likelihood of Equation 7.6:

ln L = - k ϑ k -θk 2σ 2 k - 1 2 ln(2πσ 2 k ) + N bins i=1 D i ln(Π i ) -Π i -ln(D i !) (7.6)
The first summation term of the likelihood is dedicated to nuisance parameters (ϑ k ) whose values are constrained in the fit ( θk ) with given uncertainty (σ k ). It is reported for completeness since so far it was opted to constrain no parameter in the analysis. The second term constitutes the binned Poisson loglikelihood, written under the assumption that the bin content follows Poisson statistics. The test statistic correspondingly adopted is the profile likelihood ratio (PLR) of Equation 7.7:

t σ e = -2 ln L(σ e , θ) L( σe , θ) (7.7)

The numerator of the logarithm argument represents the maximum likelihood for a specified cross section σ e , with θ the corresponding values of other free parameters. The denominator corresponds to the absolute maximum likelihood, with σe and θ maximum likelihood estimators for cross section and other free parameters. The PLR is chosen to minimize the probability of type II error (non-rejection of false hypothesis), as prescribed by Neyman-Pearson lemma [START_REF] Neyman | IX. On the problem of the most efficient tests of statistical hypotheses[END_REF]. Since this analysis has no discovery potential, the profile likelihood ratio is computed under the signal hypothesis H 1 (i.e. σ e > 0 in the PCD model). The distribution of the PLR, f(t σ ), is studied in in order to predict LBC sensitivity and extract an upper limit at a 90% confidence level. In both cases, the dark matter-electron cross section such that the p-value computed on the PLR distribution is equal to 0. [START_REF] Wilks | The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses[END_REF]. In particular, they are expected to follow a non-central and conventional chi-square distributions with one degree of freedom, respectively. This was verified to be the case for f(t σ |H 1 ), in the mass range of interest. In the case of upper limit calculation, for each given mass, t σ is computed increasing σ e until σ e = σe . The asymptotic distribution f(t σ |H 1 ) = χ 2 1 is used, since the goal is finding the cross section value such that the probability of incorrectly rejecting the signal hypothesis is exactly 10%. Figure 7.7 shows a PLR scan over few cross section orders of magnitude for a background-only Monte Carlo dataset. The p-value equals 0.1 where the test statistic assumes the critical value t σ = 2.7055, at a cross section σe = 1.2 × 10 -37 cm 2 . Such value constitutes the corresponding 90% confidence level upper limit. As σ e decreases, the test statistic converges to zero, a clear sign of preference of the background-only hypothesis.

science data

The first LBC data run was carried out with CCD 6415 only, without external shielding. Important improvements were brought about in coincidence with second DAQ and shielding installation, namely lower backgrounds, transfer inefficiency and amplifier glowing. Levels of noise overall worsened. A second data run was conducted soon afterwards. Characterization work during these phases was detailed in Chapter 6. Data cleaning algorithms were optimized to reject undesired features, in particular hot regions and unexplained detector response effects. The DAQ strategy was improved for the third and fourth science data runs, the latter currently ongoing. The present section focuses on these efforts, with particular emphasis on science run 3. Preliminary results obtained with data from the latter are reported in Section 7.3. for run 4. Conservative data cleaning strategies were initially devised to cope with higher backgrounds and CTI during run 1. A cluster mask was optimized for the purpose. This work came in handy for later runs, to exclude the few observed high-energy events. A sufficient amount of data was acquired for all runs to ensure 100 g-day exposures.

Data Cleaning

Standard image processing steps were used on LBC science data with thresholds optimized for the specific DAQ strategy. The following algorithm was implemented for science run 3 data:

Data Selection

Images with outlying dark current or other anomalies are excluded.

First (prescan) and last 12 (overscan) columns are always excluded. First row is excluded from all images due to a poorly understood baseline effect.

Image Average

Image is averaged using skips in range [START_REF] Vera | Rotation of the Andromeda Nebula from a Spectroscopic Survey of Emission Regions[END_REF]640].

Pedestal Subtraction

Row by row subtraction. Pedestal estimated in the physical row region as Gaussian fit mean after excluding pixels > 2σ avg (ADU) from mean.

Image Calibration

Image is calibrated extracting k e calibration constant (ADU/e -) as a free parameter in the Gauss-Poisson convolution fit. of the corresponding inference analysis will be reported in [START_REF]First Science Results with the DAMIC-M Low Background Chamber[END_REF]. Next section reports preliminary results extracted with science run 3 data.

Cluster Reconstruction

results

The 115 g-day dataset acquired in science run 3 was used to set 90% C.L. limits on the heavy and ultra-light mediator dark matter electron scattering cross sections. Data was subdivided in eight sets, with the four amplifiers' column range roughly divided in half ( [START_REF] Bertone | A History of Dark Matter[END_REF]150]; [151,320]) to partially capture a dark current linear trend across. 2 The global best-fit yields values for background free parameters consistent among datasets and compatible with measurements reported in Section 6.2. A lower DC rate is measured in the second half of amplifiers column range, as expected from observations. Extracted 90% confidence level exclusion limits are reported in Figure 7.13 for heavy (top) and ultra-light (bottom) mediator candidates. LBC science run 3 preliminary limits are represented as a black solid line. For both cases, yet unexplored parameter space regions are excluded. In particular, this work sets world-leading limits in mass ranges [1.4, 14] MeV and [1.5, 300] MeV for heavy and ultra-light mediator dark matter, respectively. Exclusion limits from other direct detection experiments [START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF][START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF][START_REF] Aprile | Light Dark Matter Search with Ionization Signals in XENON1T[END_REF][START_REF] Aprile | Emission of single and few electrons in XENON1T and limits on light dark matter[END_REF][START_REF] Cheng | Search for Light Dark Matter-Electron Scattering in the PandaX-II Experiment[END_REF][START_REF] Agnes | Search for dark matter particle interactions with electron final states with DarkSide-50[END_REF][START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF] are included in the plots. SENSEI CCD experiment results [START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF] are recasted using halo parameters from [START_REF] Baxter | Recommended conventions for reporting results from direct dark matter searches[END_REF] and ionization yield model from [START_REF] Ramanathan | Ionization yield in silicon for eVscale electron-recoil processes[END_REF] for consistency of comparison. LBC 90% upper limits on exposure- [START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF][START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF][START_REF] Aprile | Light Dark Matter Search with Ionization Signals in XENON1T[END_REF][START_REF] Aprile | Emission of single and few electrons in XENON1T and limits on light dark matter[END_REF][START_REF] Cheng | Search for Light Dark Matter-Electron Scattering in the PandaX-II Experiment[END_REF][START_REF] Agnes | Search for dark matter particle interactions with electron final states with DarkSide-50[END_REF][START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF][START_REF] Arnaud | First Germanium-Based Constraints on Sub-MeV Dark Matter with the EDELWEISS Experiment[END_REF][START_REF] Agnese | Erratum: First Dark Matter Constraints from a Super-CDMS Single-Charge Sensitive Detector[END_REF]. Benchmark models taken from [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. normalized rates of events for 1 to 4 e -bins are (1.32e+04, 89.6, 0.882, 0.0341) in events/(g•day) units, respectively. SENSEI rates as reported in [START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF] are (525.2, 4.449, 0.255, 0.253) events/(g•day), respectively. The 4 e -bin, where LBC performance is an order of magnitude better than SENSEI's, largely contributes to the observed improvement for masses 2 MeV (about the minimum necessary mass to produce a 4 e -event). The other contributing factor is the 10 × 10 binning configuration employed in science run 3, which, as shown in Figure 7.9, leads to higher sensitivities due to better signal reconstruction.

The present results significantly improve on DAMIC at SNOLAB limits [START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF] in an even wider mass range. Few pixels with values > 6σ ro in the latter analysis lead to signal preference for masses above few MeV, thereby driving the limit.

While this analysis suffers from a similar issue, the more effective background rejection capabilities ascribable to sub-electron resolution explain the sizable improvement in said range. Plots additionally show benchmark models taken from [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. For heavy mediator, thermal freeze-out dark matter is foreseeable above the blue line. Below, the corresponding relic abundance is too large to fit observations. For ultra-light mediator dark matter, thermalization with the Standard Model is not possible. The relic abundance is formed by 2 → 2 Standard Model annihilations into dark matter (i.e. freeze-in). This requirement constrains the interaction cross-section and candidate mass along the blue line. Figure 7.14 shows heavy-and ultra-light mediator 90% C.L. exclusion limits overlaid on the LBC sensitivity forecast with ±1σ and ±2σ uncertainty bands. Since sensitivity lines are produced with an incomplete background model, limit is not expected to accurately match them. In particular, at high masses the limit deviates from the sensitivity by more than +2σ due to few

3-e -and one 4-e -count. These results have been cross-validated with the independent framework built by DAMIC-M collaborators.

In view of science run 4 data, work is ongoing to develop a more accurate background model, particularly in terms of detector response application, to better address dark current non-uniformities and correlated noise. In general, in order to achieve discovery potential, substantial efforts will be devoted to construct a thorough background model for sub-GeV dark matter searches with DAMIC-M. Systematic sources of uncertainty are also to be studied.

Among these, analysis quantities (e.g. halo model parameters, physical signal rates, diffusion model, etc.) and instrumental effects (e.g., calibration fluctuations, amplifier light, temperature dependence, etc.) are expected to have a sizable effect. The preliminary results reported in this chapter demonstrate nevertheless the highly competitive nature of DAMIC-M skipper charge-coupled devices as direct dark matter detectors. search was subsequently conducted in the latter energy range. The analysis threshold was set to 50 eV ee . The background model was found to be consistent with data all the way down to 200 eV ee , which validates the methodology employed for its construction. Exclusion limits were set on the spinindependent WIMP-nucleon scattering cross section, despite fit's preference for a bulk exponential excess below 200 eV ee . This will be further investigated with DAMIC-M skipper CCDs at SNOLAB and LSM. These are the most stringent limits from a silicon target detector between 1 and 9 GeV/c 2 . DAMIC-M advances broaden the accessible parameter space for CCD dark matter searches. A kg-scale mass goal requires optimal yield of science-grade sensors. Substantial research and development are conducted in this direction.

A cryogenic test chamber was set up at LPNHE, in a cross-institutional effort to conduct systematic CCD testing and design a protocol to establish detector grade for DAMIC-M (pre-)production CCDs. Chapter 4 detailed first results from pre-production testing. CCDs from the entire batch generally showed science-grade performance, except for the presence of extended hot regions affecting a sizable fraction of the pixel array in all devices. This motivated the review of some stages of manufacturing at DALSA facilities. Preliminary results from the second pre-production batch are promising in this respect.

The construction of LPNHE cryogenic test chamber was thoroughly described in Chapter 5. This work spans the range of experimental activities essential to set up a dark matter detection apparatus. Cryogenic and electronic instrumentation was assembled and extensively tested before detector deployment. The system was provided with full remote control capabilities by The mass range spanned by dark matter candidates.

Salient families and the range they cover are reported.

Adapted from [START_REF] Battaglieri | US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report[END_REF] . . . . . . . . . . . . . . . . . . . . . . from [START_REF] Marrodán | Dark matter directdetection experiments[END_REF]. The salient addition relative to reference [START_REF] Marrodán | Dark matter directdetection experiments[END_REF] is that shown signal channels all have potential for sub-GeV dark matter detection (see e.g. [START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF][START_REF] Derenzo | Direct detection of sub-GeV dark matter with scintillating targets[END_REF]). . . . . . . 14 1 (dotted), 10 (dashed), and 100 (solid) GeV/c 2 . F 2 SI (E R ) = 1 and σ χn = 10 -36 cm 2 is assumed. Plot is meant to show scattering rate dependence on kinematic factors. 17 Few hot regions can be seen for both amplifiers. . . . . 180

  Sorbonne Université -Faculté des Sciences et Ingénierie École doctorale des Sciences de la Terre et de l'Environnement et Physique de l'Univers de Paris -ED 560 Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE) -UMR 7585R E C H E R C H E D E M AT I È R E N O I R E L É G È R E E T E X P L O R AT I O N D U S E C T E U R C A C H É AV E C L ES D I S P O S I T I F S À T R A N S F E R T D E C H A R G E S D E D A M I C AT S N O L A B E T D A M I C -M Thèse présentée par michelangelo traina en candidature pour le diplôme de doctorat en physique de l'univers Dirigée par dr. antoine letessier-selvon dr. romain gaïor Soutenue à Paris le 7 octobre 2022 devant le jury composé de: prof. christophe balland, Sorbonne Université, Paris President prof. laura baudis, Université de Zurich Rapporteure dr. federica petricca, Institut Max Planck, Munich Rapporteure prof. corinne augier, Université Claude Bernard Lyon 1 Examinatrice prof. paolo privitera, Université de Chicago Examinateur Sorbonne University -Faculty of Science and Engineering Doctoral School of Earth and Environmental Sciences and Physics of the Universe of Paris -ED 560 Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE) -UMR 7585S E A R C H F O R L I G H T D A R K M AT T E R A N D E X P L O R AT I O N O F T H E H I D D E N S E C T O R W I T H T H E D A M I C AT S N O L A B A N D D A M I C -M C H A R G E -C O U P L E D D E V I C E SThesis presented by michelangelo traina in candidacy for the degree of doctor of philosophy in physics of the universe Supervised by dr. antoine letessier-selvon dr. romain gaïor Defended in Paris on October 7th, 2022 before the committee comprised of: prof. christophe balland, Sorbonne University, Paris President prof. laura baudis, University of Zurich Referee dr. federica petricca, Max Planck Institute, Munich Referee prof. corinne augier, Claude Bernard Lyon 1 University Examiner prof. paolo privitera, University of Chicago Examiner R É S U M É L'existence dans l'Univers de matière non baryonique électromagnétiquement inerte est étayée par plusieurs d'observations astrophysiques et cosmologiques.

4 GeV/c 2 )

 42 de simulations GEANT4 des contaminations radioactives dans une géométrie virtuelle du détecteur. Les activités sont contraintes avec mesures de dosages effectuées sur les différents composants du détecteur. Par ailleurs, une technique d'analyse de coïncidence spatiale unique aux CCD est exploitée pour quantifier les isotopes primordiaux et cosmogéniques distribués sur la surface et dans la masse du CCD. Certaines des mesures effectuées de cette manière surpassent largement les méthodes de dosage les plus courantes. Le modèle xi de fond est utilisé pour rechercher des WIMP légers à partir d'un ensemble de données correspondant à une exposition de 11 kg-jour. Malgré un excès statistiquement significatif d'événements d'énergie inférieure à 200 eV, cette analyse place la limite d'exclusion la plus forte sur la section efficace de diffusion WIMP-nucléon indépendante du spin avec un détecteur cible en silicium pour masses < 9 GeV/c 2 . DAMIC-M est sur le point de franchir des étapes technologiques importantes vers ses objectifs scientifiques. Le déploiement de CCD skipper avec une électronique développée au LPNHE abaissera les seuils de détection à moins d'une dizaine d'eV, permettant simultanément une caractérisation plus précise du détecteur. Des cryostats de tests sont mis en place pour effectuer des évaluations systématiques des CCD et concevoir un processus de sélection pour DAMIC-M. Au LPNHE, un cryostat a également été utilisé pour la mise en service de l'instrumentation de l'expérience prototype LBC au LSM. La LBC à été mise en service fin 2021. Le bruit électronique (∼10 e -) et le courant de fuite (∼10 -3 e -/pixel/jour) élevés mesurés par rapport aux détecteurs de SNOLAB, mettent en évidence deux revers potentiels pour DAMIC-M. Malgré tout le premier ensemble de données scientifiques acquis avec les CCD skipper de la LBC (∼20 g) permettent de définir des limites d'exclusion de classe mondiale sur la section efficace de diffusion de la matière noire sur les électrons. xii A B S T R A C T The existence of electromagnetically inert non-baryonic matter in the Universe is supported by a plethora of astrophysical and cosmological observations. Dark matter is expected to account for more than 80% of the mass of the Universe. A vast bestiary of particle candidates have been theorized, with the Weakly Interacting Massive Particle (WIMP) paradigm dominating the landscape thanks to its desirable features. Experimental efforts of the last decades have been unsuccessful in detecting WIMPs with weak-scale masses (10 -10 , thus motivating the search for lighter dark matter. The DAMIC (DArk Matter In CCDs) experiments aim for direct detection of light WIMPs and hidden sector candidates by means of thick silicon Charge-Coupled Devices (CCDs). DAMIC at SNOLAB ∼40 g detector sits beneath a 2070 m rock overburden in the Vale Creighton Mine in Canada. Its CCDs are characterized by electronorder readout noise, minimal leakage current (∼10 -4 e -/pixel/day) and excellent spatial resolution (∼15 µm). The DAMIC-M kg-scale detector will be hosted in the cleanroom facilities of the Laboratoire Souterrain de Modane (LSM), 1700 m below the Fréjus peak, in France. Its CCDs additionally feature skipper readout amplifiers, which enable sub-electron resolution by means of repeated non-destructive charge measurements. DAMIC-M background goal is 0.1 dru (0.1 events per keV-kg-day), which represents a two orders of magnitude leap relative to SNOLAB apparatus. This thesis work delves into two major themes: the construction of the first comprehensive CCD background model in the context of DAMIC at SNO-LAB, and the research and development efforts towards DAMIC-M science goals, particularly with the deployment of its prototype detector, the Low Background Chamber (LBC). The DAMIC at SNOLAB background model is constructed by performing GEANT4 simulations of radioactive contaminants in a virtual detector geometry. Activities are constrained by means of different assay methods. Notably, the spatial coincidence analysis technique unique to Charge-Coupled Devices is leveraged to quantify notorious primordial and cosmogenic isotopes distributed over CCD surface and bulk. Some of the measurements conducted in this fashion vastly outperform more common assay methods. The background model is used to search for light WIMPs in a 11 kg-day exposure dataset.

3. 3 . 2 A 4 . 1 . 1 4 . 1 . 2 1 D

 324114121 11 kg-day WIMP search . . . . . . . . . . . . . . . . . . 4 the damic-m experiment 4.1 DAMIC at Modane . . . . . . . . . . . . . . . . . . . . . . . . . . Skipper CCDs . . . . . . . . . . . . . . . . . . . . . . . . . The DAMIC-M Detector . . . . . . . . . . . . . . . . . . . 4.2 R&D towards DAMIC-M Science Goals . . . . . . . . . . . . . . 4.2.1 CCD Yield Optimization . . . . . . . . . . . . . . . . . . . 4.2.2 Background Mitigation . . . . . . . . . . . . . . . . . . . xv A R K M AT T E R Well-established astrophysical and cosmological evidence suggests that the majority of the Universe mass content consists of a stable non-luminous component known as Dark Matter. A fundamental element of modern Cosmology, Dark Matter is indispensable to propose an accurate model of the structure and evolution of the Universe. As intended nowadays, the concept was put forward in the 1930's. However, mentions of dark astronomical objects curving the trajectory of light date back to XIX century studies of stellar dynamics in the local Milky Way [1].

Figure 1 . 1 :

 11 Figure 1.1: False color mosaic of the Coma cluster. Two large elliptical galaxies, NGC 4889 and NGC 4874, dominate the cluster's center. The mosaic combines visible-light data from the Sloan Digital Sky Survey (color coded blue) with infrared views (red and green, respectively) from NASA's Spitzer Space Telescope. Credits: NASA/JPL-Caltech/L. Jenkins (GSFC)

Figure 1 . 2 :

 12 Figure 1.2: The spiral galaxy NGC2403 (left) and its rotation velocity profile (right).

Figure 1 . 3 :

 13 Figure 1.3: Collage showing six different galactic clusters collisions taken with Hubble Space Telescope (HST) and Chandra X-ray Observatory. The postcollision distribution of stars and dark matter (blue shades) was extracted

Figure 1 . 4 :

 14 Figure 1.4: Visual illustration of the multipole expansion of the cosmic microwave background temperature distribution. Credits: [25].

Fig- ure 1 . 4

 14 shows a visual representation of the multipole decomposition of the CMB temperature distribution.

Figure 1 . 5 :

 15 Figure 1.5: CMB power spectrum measured by the Planck collaboration [26]. The ΛCDM spectrum best fit is plotted in light blue. Residuals with respect to this model are shown in the lower panel. The error bars show ±1σ uncertainties. The vertical scale changes at l = 30, where the horizontal axis switches from logarithmic to linear.

Figure 1 . 6 :

 16 Figure 1.6: The mass range spanned by dark matter candidates. Salient families and

Figure 1 . 7 :

 17 Figure 1.7: Comoving number density Y (left) and resulting thermal relic density (right) of a 100 GeV/c 2 , P-wave annihilating dark matter particle as a function of temperature T (bottom) and time t (top). The solid contour is

Figure 1 . 8 Figure 1 . 8 :

 1818 Figure 1.8: Feynman diagram illustration of dark matter detection strategies. The arrow sets time direction and identifies the detection strategy.

Figure 1 . 10 :

 110 Figure 1.10: Differential scattering rates for silicon (red), argon (blue), germanium (black), and xenon (green), for WIMP masses: 1 (dotted), 10 (dashed), and 100 (solid) GeV/c 2 . F 2 SI (E R ) = 1 and σ χn = 10 -36 cm 2 is assumed. Plot is meant to show scattering rate dependence on kinematic factors.

( 10 -

 10 10 4 GeV/c 2 ). The experiments leading this search are noble-liquid time projection chambers. At lower masses, in the so-called light WIMP parameter space (0.1 -10 GeV/c 2 ), semiconductor detectors and bolometers compete for the highest sensitivity. Current best limits and expected sensitivities of upcoming experiments are reported in Figure 1.11.

Figure 1 . 11 :

 111 Figure 1.11: The WIMP search landscape. Current best exclusion limits (from a variety of experiments) are given by the gray dashed line. Sensitivity projections are presented as solid lines. TPC experiments are approaching the neutrino floor (fog)[START_REF] Billard | Implication of neutrino backgrounds on the reach of next generation dark matter direct detection experiments[END_REF][START_REF] Ciaran | New Definition of the Neutrino Floor for Direct Dark Matter Searches[END_REF], where a potential dark matter signal will

Figure 1 . 12 :

 112 Figure 1.12: Dark matter-electron scattering sensitivities for heavy mediator dark matter in silicon (solid) and germanium (dashed) targets of 1 (blue), 5(green) and 10 (red) electrons. Solid black line shows exclusion limits from XENON10[START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF] for reference. Credits:[START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF].

  indices, corresponding to the ŷ and x directions, respectively. A 1k × 6k CCD has (about) 1000 columns and 6000 rows. CCDs typically have four readout amplifiers at the corners of the pixel grid, which can be used individually or collectively to acquire images. The four functioning stages of a CCD are: charge production, collection, transfer and readout[START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]. Signal charge is produced by means of photoelectric effect and/or inelastic scatterings, promoting carriers to the conduction and valence bands of the semiconductor wafer.Carriers are then drifted by means of an applied substrate voltage across the thickness of the device, and stored at shallow depth (less than a micrometer below the surface electrodes) in the surface of the CCD. The pixel structure is achieved column-wise by means of physical implants called channel stops, and row-wise using three voltage gates, called parallel clocks, whose voltages are tuned to create a potential well for the collection phase. Parallel clocks also serve to transfer charge across different rows of pixels of the CCD, in the direction of the outermost row(s), where readout amplifiers are located.

Figure 2 . 1 :

 21 Figure 2.1: A DAMIC 4k × 4k CCD in its copper module, ready to be installed in the DAMIC apparatus. The Kapton cable transports clock, bias and video signals to/from the CCD.

  Outer-shell electrons can populate the valence band and the conduction band. Electrons in the valence band are bound to atoms and form covalent bonds with their counterparts from other atoms of the crystal. Electrons in the conduction band are free to roam about the crystal. A forbidden energy gap separates the two bands: no energy levels are found across the gap in the case of a pure semiconductor. 1In practice no semiconductor is absolutely pure. Two particularly important kind of impurities are donor and acceptor impurities. These are atoms having respectively one more or one less valence electron relative to the semiconductor atom. Silicon has four valence electrons: common donor and acceptor impurities are phosphorous and boron, which have five and three, respectively. Impurities introduce energy levels across the energy gap close to the conduction and valence band, respectively. This is because for each donor or acceptor atom, there is one unpaired electron or hole (i.e., lack thereof). Figure 2.2 shows the band structure of intrinsic silicon and silicon with donor impurities. The presence of a pentavalent phosphorous atom introduces a discrete energy level 0.05 eV away from the conduction band. A similar situation occurs when introducing trivalent boron atoms. In such case, the correspond-

Figure 2 . 2 :

 22 Figure 2.2: Band structure for pure silicon and silicon with donor impurities. The energy gap between valence and conduction bands spans about 1.16 eV.The presence of a phosphorous atom introduces a discrete energy level 0.05 eV from the conduction band.

Figure 2 . 3 .Figure 2 . 3 :

 2323 Figure 2.3: Representation of an np junction. Electron (blue) and hole (red) concentrations dominate on opposite sides. They gradually fall off across the junction and become subdominant. The net effect is the formation at the junction of an electrically charged region depleted of mobile charges (delimited by dashed lines). Red and blue shaded areas have positive and negative net charge densities, respectively.

Figure 2 . 4

 24 illustrates the structure of a DAMIC CCD pixel. Electron-hole pairs are produced in the so-called photo-sensitive volume by ionizing radiation. The photo-sensitive volume consists of high-resistivity ( 10 kΩ•cm) phosphorous-doped n-type silicon, whose low donor concentration (∼10 11 cm -3 ) allows full depletion at reasonably low values of substrate

Figure 2 . 4 :

 24 Figure 2.4: Pixel cross sectional view. The pixel is akin to a MOS capacitor consisting of polysilicon metal gate electrodes interfaced to a pn-junction by means of a silicon insulator compound.

Figure 2 . 5 Figure 2 . 5 :

 2525 Figure 2.5 shows a cross-sectional view of a DAMIC CCD pixel and the potential profile across its thickness. The shape of the profile is the result of an interplay between applied gate voltage and substrate voltage, although the value at the well minimum is independent of the latter [84]. The electron-hole pairs produced by ionization in the active region are drifted in the direction of the electric field, ẑ. Holes head towards the buried channel where they are held until transfer, electrons toward the backside contact where substrate voltage is applied. Holes are the signal DAMIC CCDs read out: electrons are not

Charge Transfer -The 3 -

 3 Phase Polysilicon Gate Charge transfer across rows and columns of charge-coupled devices is achieved by varying in time the three voltage signals delivered at each pixel gate. The clocks transferring charge across one column (i.e., in the row direction) are called parallel clocks. The clocks transferring charge across one row (i.e., in the column direction) are called serial clocks. An example of clock sequencing is shown in Figure 2.6. The right-hand side image shows the clock sequence, where the three gate voltages are switched between a high and low states, allowing charge to redistribute over different regions. The basic sequence slices consist in lowering a clock voltage to allow charge over the region it controls,

Figure 2 . 6 :

 26 Figure 2.6: Transfer across two pixels in the ŷ direction. The clocking sequence is shown on the right-hand side. State 1 shows the pixel accumulation phase. State 2 shows clock 1 set to low with charge redistributing accordingly. In state 3, clock 2 is set high and charge gathers in the clock 1 region. Similar sequencing is employed to get to state 7, that completes transfer across the two neighboring pixels. Left-hand side top and bottom images show charge (pixel structure not to scale) during states 1 and 7, respectively.

Figure 2 . 7 :

 27 Figure 2.7: Salient elements of charge transfer. A fraction of a CCD grid is shown with a readout amplifier in the bottom right corner. In order to get to the readout stage, charge is transferred across different rows by means of parallel clocks. No transfer occurs across the horizontal direction in ordinary rows thanks to implanted channel stops. The last vertical transfer occurs across the transfer gate: a potential barrier meant to control charge flow to the serial register. Charge in the outermost row -the serial register -is transferred towards the readout amplifier by means of fast serial clocks.

Figure 2 . 8 Figure 2 . 8 :

 2828 Figure 2.8: Top: CCD readout stage micrograph. Image courtesy of PNNL (Pacific Northwest National Laboratory). Key components are labeled. Bottom: Circuit diagram of CCD readout. SW controls charge flow across the output gate. Reset switch clears charge in the buried channel. Output transistor amplifies the measured voltage. CCD layer structure not to scale.

3

  Accumulating charge from multiple pixels is referred to as binning. Data acquired by accumulating charge from 10 pixels has a serial binning equal to 10. Binning is possible in the parallel direction too. In such case, charge is accumulated in the serial register prior to readout.A 10 × 20 image has serial binning equal to 10 and parallel binning equal to 20.

Figure 2 . 9 :

 29 Figure 2.9: Top: Conventional CCD video output trace (drawing). The summing well pulse pinpoints pixel charge injection from the summing well into the sense node. Typical values for the integration time are between 10 µs and 100 µs. Reset and summing well pulse amplitudes are typically between 1 V and 10 V. Bottom: Comparison of CDS performed with strong high-and low-frequency noise components. CDS integration significantly suppresses high-frequency noise components, but is not effective against low-frequency noise.

Figure 2 . 10 :

 210 Figure 2.10: White (red) and flicker (teal) noise spectra. Below 1 kHz, flicker noise is up to a factor of 10 larger than flat-spectrum white noise. Above 1 kHz white noise takes over; flicker noise sets the CCD noise floor.

  Glowing dark counts are generated by infrared light emitted by the output amplifier. This effect increases with the readout drain voltage V DD . More recently the DAMIC-M collaboration found evidence for light generation by other CCD components like readout clocks (see Chapter 6).

Figure 2 .

 2 11 shows a portion of CCD image strongly affected by glowing. The amplifier light is visible as a background gradient in both the vertical and horizontal directions. Several particle tracks also appear as clusters of pixels (dark-grey/black in color) with different topology.

Figure 2 . 11 :

 211 Figure 2.11: Portion of CCD image affected by amplifier glowing. IR light events are visible as a background gradient in both the vertical and horizontal directions. Several particle tracks also appear as black clusters of pixels with various different shapes.

Figure 2 .

 2 Figure 2.12 shows a portion of CCD image featuring significant serial CTI. Charge belonging to the particle track is considerably smeared in the horizontal direction. CTI in DAMIC CCDs is less than one part in 10 millions. This does not affect DAMIC science reach since the uncertainty on the pixel value from output amplifier noise and dark current dominates.

Figure 2 . 12 :

 212 Figure 2.12: CCD image track zoom-in. The image is affected by significant serial charge transfer inefficiency. Charge belonging to the particle track is smeared in the horizontal direction. Image equalization is chosen to emphasize track and associated CTI against noise in the background

Figure 2 . 13 :

 213 Figure 2.13: Calibrated pixel charge distribution of a low-background CCD image.

Figure 2 . 14 :

 214 Figure 2.14: Top: Tracks in a fraction of CCD image. Noise can be observed in the rest of the image as pixel value fluctuates about the pedestal (i.e., the value of a pixel empty of charge in ADU). The bottom scale correlates the pixel value in ADU to its color in the image. Bottom: 50 × 50 pixels portion of CCD image. Cluster topologies associated to various particles interacting with the CCD are shown and labeled. The muon track extremities have different widths by virtue of the different interaction depths. Only pixels with energy > 0.1 keV are colored for improved contrast.

Figure 2 . 15 :

 215 Figure 2.15: The DAMIC at SNOLAB apparatus. (a) The 4k × 4k CCD in its copper tray. (b) The IR-shield OFHC copper box. The uppermost CCD, Extension 1, is sandwiched between two Roman lead blocks (c) The in-vacuum components and the copper vacuum vessel. (d) The 20 cm lead castle and the 42 cm polyethylene shielding.

Figure 2 . 16 :

 216 Figure 2.16: xẑ and x ŷ (pixel plane) cross-sectional views of charge diffusion in a CCD. The amount of charge in different pixels is represented with shades of red: darker corresponds to more charge.

  shows the DAMIC diffusion model extracted for the 1 × 100 binning of the latest 11.6 kg-day science dataset. The ee sub-

Figure 2 . 17 :

 217 Figure 2.17: DAMIC diffusion model. The reconstructed cluster spread is related to the interaction depth using cosmic muon tracks (dashed line). The baseline model uncertainty band (E = 0 keV ee ) and solid lines accounting for linear energy corrections at E = 10, 20 keV ee are shown. Energies are expressed in electron-equivalent units.

Figure 2 . 19 :

 219 Figure 2.19: Ionization energy signal in keV ee as a function of recoiled nucleus energy in keV nr . DAMIC results are reported as a dashed line. The gray band represents the 1σ uncertainty range. Previous low-energy measurements and the expected values from the Lindhard model are also reported.

Figure 2 . 20 :

 220 Figure 2.20: Mean pedestal-subtracted pixel value in ADU as a function of the row number. Dataset acquired with 1 × 100 binning. Rows up to 42 show a non-zero mean pixel value; past 42, in the vertical overscan, they are consistent with zero. The higher amount of charge seen for CCDs 2 and 7 can be ascribed to light leaks inside the copper box.

Figure 2 .

 2 Figure 2.20 shows the charge profile in the seven operational DAMIC CCDs after processing the images for DC estimation. The higher amount of charge seen for CCDs 2, 6 and 7 was ascribed to light leaks inside the copper box.

  The present chapter served as a comprehensive introduction to the DAMIC at SNOLAB experiment. The working principles of its detectors and the design of its apparatus have been reviewed, in order to prepare the reader for the technical discussion due in the next chapter. By necessity, only the salient information on calibration activities was provided. Chapter 3 is devoted to the construction of the radioactive background model of DAMIC at SNO-LAB and the subsequent search for light WIMPs conducted on a 11.6 kg-day dataset acquired over 2017 and 2018. T H E D A M I C AT S N O L A B B A C K G R O U N D M O D E L The most remarkable achievement of DAMIC at SNOLAB is the construction of the first comprehensive CCD background model. This work was conducted with data acquired during the second stage of the experiment. It was finalized and published in 2021. The background model was used to search for light WIMPs in the 1-10 GeV/c 2 mass range. The details of this effort are the subject of the present chapter. The chapter is divided into three parts. Section 3.1 discusses stage 2 data and its processing. Section 3.2 is devoted to background mitigation and rejection, focusing in particular on the measurements and simulations of radioactive contaminants in the DAMIC apparatus. Section 3.3 details the construction of the background model and the WIMP search result. The contents of this chapter are thoroughly described in three papers published on peer-reviewed journals [58, 75, 104].

Figure 3 . 1 :

 31 Figure 3.1: Portion of image acquired with two amplifiers of the same serial register. Correlated noise is visible as a diagonal pattern. The different background shade in the two images corresponds to the respective digitizer pedestals (i.e., the 0-charge signal).

  are constructed for individual CCDs and data runs. For each run, median and median absolute deviation (MAD) of each pixel in all images are computed. Pixels which are more than 3 MAD away from the median in at least half of the images or have outlying ( 5σ) median or MAD are excluded. One single iron mask is eventually constructed for every CCD by combining masks obtained separately for 35 distinct data runs. Higher temperatures runs (150 K and 170 K) are exploited to take advantage of the dark current temperature dependence. The final iron mask represents the logic sum of masks from individual runs. Isolated pixels masked in a single run only are not excluded. The iron mask removes on average 6.5% of pixels from a CCD. The remaining 93.5% is employed for this analysis.Figure 3.2 shows the iron masks extracted for the 7 operational DAMIC CCDs.

Figure 3 . 2 :

 32 Figure 3.2: Iron masks for the 7 DAMIC CCDs. Masked pixels are represented in blue, retained pixels are represented in red.

Figure 3 . 3 Figure 3 . 3 :

 3333 Figure 3.3 displays the event E-σ x distribution of the 1 × 100 DAMIC science data. The energy range reported in the plot includes the full interval used in the WIMP search, i.e., 0.05-6 keV ee . The background model construction was carried out between 6 and 20 keV ee in order to include the full tritium spectrum. The model was extrapolated below 6 keV ee to conduct a profile likelihood ratio test. The details of this analysis are the subject of Section 3.3.

Figure 3 . 4

 34 Figure 3.4 shows the ∆LL distributions for data and blanks (null exposure images) with simulated Poisson dark current. The threshold for this analysis is ∆LL = -22, where the statistics of expected noise clusters crosses 0.1.

Figure 3 . 4 :Figure 3 . 5 :

 3435 Figure 3.4: Log-likelihood ratio distributions for data (red points) and blank images with simulated Poisson dark current (gray points). The chosen analysis threshold is ∆LL = -22, where expected noise clusters are less than 0.1.

  Simulations are then compared to experimental data outside the WIMP search energy region of interest to construct the background model. As previously remarked, this analysis is performed in the E-σ x space, exploiting the excellent energy and depth resolution of CCDs. The following Section 3.2.1 explores the landscape of background sources that affect DAMIC detectors. Section 3.2.2 covers the assays conducted for certain detector parts and isotopes, and motivates the assumptions made to constrain the background model. These sections lay the grounds for an in-depth discussion of the simulation work in Section 3.2.3. Section 3.2.4 provides a thorough account of the measurement of in-CCD contaminants, used to inform the background model construction. Partial charge collection (PCC),

Figure 3 . 6

 36 Figure 3.6 shows a cross section of the GEANT4 model of the DAMIC at SNO-LAB apparatus. Detector parts are colored according to the grouping used in the background model construction (see Section 3.3). The total number of volumes used in the geometry is 190, of which 74 are unique. The geometry can be conveniently subdivided in the following groups of detector parts:

Figure 3 . 6 :

 36 Figure 3.6: Cross-sectional view of the GEANT4 geometry of the DAMIC at SNOLAB detector. Detector parts are colored according to material and background model grouping. Copper parts are 3D-rendered making use of a color gradient. A blow-up of a CCD module with modified aspect ratio is displayed at the bottom.

Figure 3 . 7 :

 37 Figure 3.7: DAMIC at SNOLAB CCD sensor geometry. CCD dimensions are reported in the text. The various layers are colored according to their material.

Figure 3 . 7 illustrates

 37 the layered CCD structure implemented in the geometry. The sensitive volume (CCD bulk) measures 61.74 mm × 61.92 mm × 669 µm and is laterally centered in a rectangular silicon block of size 64.36 mm × 63.99 mm × 674.2 µm. The frontside dead region consists of (top to bottom) a silicon dioxide insulating layer (1.6 µm), the triple polysilicon gate (0.3 µm) and another thin silicon nitride insulating layer (0.1 µm). The physical frontside dead layer is shown in Figure 3.8 for comparison with its simulated counterpart. The backside dead region consists of an In-Situ Doped Polysilicon (ISDP) gettering layer (1.0 µm), a silicon nitride insulating layer (0.1 µm), and three alternating layers of polysilicon (0.4 µm each) and silicon dioxide (0.3 µm each).

Figure 3 . 8 :

 38 Figure 3.8: Physical CCD frontside. The polysilicon gates lie on a thin dielectric layer (silicon nitride) and are insulated from each other with thermally laid silicon dioxide. An additional layer of silicon dioxide is deposited on top.Image courtesy of LBNL MicroSystems Lab.

Figure 3 . 9 :

 39 Figure 3.9: Results from secondary ion mass spectrometry screenings of a DAMIC CCD. Solid (dashed) lines represent measurements done with a fine (coarse) beam width. Shaded areas represent the layered backside structure as extracted from these measurements. From left to right, alternating SiO 2 /polysilicon layers are shown in red/gray, silicon nitride in yellow, ISDP getter in blue and low donor concentration n-type silicon in green.

Figure 3 . 10 .

 310 Figure 3.10. Isotopes 210 Pb and 210 Bi are simulated on front and back surface of the CCD, and in the back of the sensitive volume only, since 10 µm were removed from its frontside prior to application of the dead layers.

Figure 3 . 10 :

 310 Figure 3.10: Depth distribution of surface contaminants. The analytical form of the distribution is reported in figure.

Figure 3 .Figure 3 . 11 :

 3311 Figure 3.11: GEANT4 standard (black) and reduced (red) energy spectra for 60 Co simulated in copper module base (bottom) plate. The two histograms are compatible within statistical uncertainties. This is better seen considering their ratio reported in the bottom plot. Ratio fluctuations increase as bin statistics decreases.

Figure 3 . 13 :

 313 Figure 3.13: Neutron production rates from 238 U spontaneous fission (top) and alpha-induced neutron ejection (bottom) in different detector parts. The VIB contribution dominates in both cases.

Figure 3 .Figure 3 . 14 :

 3314 Figure 3.14: Wireframe representation of the GEANT4 geometry used to study neutrons produced in the apparatus. The VIB board is labeled in green.

2017Figure 3 . 15 :

 315 Figure 3.15: Top: Discrimination of alphas (triangles) and betas (circles) by means of f pix . Bottom: Discrimination of plasma (orange triangles) and bloomed (purple triangles) alphas using σ x /σ y .

E 1 210Bi → 210 Po + β 2 Figure 3 . 16 :

 12316 Figure 3.16: A spatially-correlated 210 Pb-210 Bi candidate decay pair. The first cluster has energy E = 57 keV. The second cluster has energy E = 376 keV with a time separation of ∆t = 1.4 d.

ure 3 . 9 )

 39 alters charge transport and leads to recombination. Properties such as carrier mobility, lifetime and electric field profile are affected[START_REF] Jesús | Modelling of minoritycarrier transport in heavily doped silicon emitters[END_REF][START_REF] Chih Hsin | Temperature dependence of minority hole mobility in heavily doped silicon[END_REF]. Numerical studies are conducted to model charge collection efficiency in CCDs

Figure 3 . 17 :

 317 Figure 3.17: Charge collection efficiency model extracted with simulations (solid) and silicon transport properties (dashed). Sensitive region (wafer) starts in correspondence with the vertical dotted gray line. Normalized units are used: 10 20 cm -3 (donor concentration), 55 × 10 9 µm 2 /(V•s) (mobility), 0.1 V/µm (electric field), and 1.2 × 10 5 s (lifetime).

8. 8

 8 µm, charge collection can only be induced by diffusion, and given the reduced lifetime, a fraction of ionization-produced carriers recombines and goes uncollected. Offset and slope of collection efficiency are not well constrained by this study. Using the model in detector response simulations introduces a large systematic uncertainty. To quantify this, both parameters are varied. It is found that a phenomenological parametrization well describes the difference between varied and nominal model of the charge collection efficiency:

  10) where C 0 n is the expected value of the nth template coefficient with uncertainty σ n from the measurement of the activity. Upper limits are only used when the unconstrained fit predicted value exceeds them. Tritium and lead-210 activities are left unconstrained, given substantial uncertainties in their quantity and spatial location. Calculated activation values are assigned a 10% uncertainty. Bins with ν ij equal to zero are discarded and their contribution to the log-likelihood is set to zero. The two-dimensional background model in the E-σ x space is obtained by minimizing -LL with CCDs 2-7 data. CCD 1 background model is constructed using the best-fit coefficients and simulation output for CCD 1. Figures 3.18 and 3.19 show the background model energy and sigma projections for CCDs 2-7 (top) and CCD 1 (bottom), respectively.

Figure 3 . 18 :

 318 Figure 3.18: Data and background model energy projections for CCDs 2-7 (top) and CCD 1 (bottom). Template material histograms are represented in different colors. The region around 8 keV ee is masked due to the inability to model the copper fluorescence line with GEANT4.

  ure 3.21). This cannot be accounted for by the systematic on partial charge collection, which preferably populates the high-sigma (backside) region.• Frontside events.Excluding a large fraction of frontside events returns a statistically significant signal with s and ε values compatible with the joint fit.• Local significance.Arbitrarily offsetting signal components across the [0.05, 6] keV ee range does not result in any statistically significant excess above 200 eV ee .

Figure 3 . 20 :Figure 3 . 21 :

 320321 Figure 3.20: Data points (black) overlaid on best-fit energy projection (red) for energy in [0, 6] keV ee . Background-only energy projection (blue) is also shown. Silicon fluorescence region between 1.6 and 1.8 keV ee is masked in the fit. The distribution of events is consistent with the background-only hypothesis down to 200 eV ee .

Figure 3 . 22 :

 322 Figure 3.22: DAMIC at SNOLAB 90% C.L. upper limit on spin-independent WIMPnucleon scattering cross section (solid red line). The background-only forecast ±σ band is shown in light red. Exclusion limits (90% C.L.) from DAMIC previous result[START_REF] Aguilar-Arevalo | Search for low-mass WIMPs in a 0.6 kg day exposure of the DAMIC experiment at SNOLAB[END_REF], other experiments[START_REF] Abdelhameed | First results from the CRESST-III low-mass dark matter program[END_REF][START_REF] Aprile | Light Dark Matter Search with Ionization Signals in XENON1T[END_REF][START_REF] Agnes | Low-Mass Dark Matter Search with the DarkSide-50 Experiment[END_REF][START_REF] Amole | Dark matter search results from the complete exposure of the PICO-60 C 3 F 8 bubble chamber[END_REF][START_REF] Agnese | Search for low-mass dark matter with CDMSlite using a profile likelihood fit[END_REF], and the 90% C.L. contours for the WIMP-signal interpretation of the CDMS silicon result[START_REF] Agnese | Silicon Detector Dark Matter Results from the Final Exposure of CDMS II[END_REF] are shown.

Figure 4 . 1 Figure 4 . 1 :

 4141 Figure 4.1: Illustration of the floating diffusion gate. Charge is sensed as a voltage pulse at the output transistor and then flushed out closing the reset switch, setting the buried channel to the reference voltage, V R . Figure adapted from [80].

Figure 4 . 2 :

 42 Figure 4.2: Working principle of a skipper amplifier. Charge is injected into the summing well (SW) from the serial register (SR). The SW pulse creates a temporary potential ladder allowing charge into the sense node (SN), kept at reference voltage V R . After integration, the output gate (OG) is put into its low state, letting carriers back to SW. It then goes back to its high configuration. A SW pulse reinitiates the non-destructive charge measurement cycle.

Figure 4 . 3 shows a micrograph of a 47 / 6

 43476 skipper amplifier.2 Serial clock and bias lines, as well as reset and readout transistors are labeled.Flicker noise sets the noise floor in conventional CCDs, which demonstrably cannot be lowered further than 1 e -[START_REF] Janesick | Scientific Charge-coupled Devices[END_REF]. Skipper CCDs break the one

Figure 4 . 3 :

 43 Figure 4.3: Skipper amplifier 47/6 50× magnification. Clock and bias lines are labeled in black. Additional skipper voltages dump gate (DG) and drain are visible on the right-hand side of the sense node. The sense floating gate is embedded in silicon oxide, between output gate (OG) and dump gate (DG). Taken at the Pritzker Nanofabrication Facility of the University of Chicago.

Figure 4 . 4 :

 44 Figure 4.4: Skipper image resolution measurements for increasing number of skips. The dashed line corresponds to the expected 1/ N skips trend. Red points are measurements of the resolution for number of skips from 1 to 1000.

Figure 4 . 4

 44 Figure 4.4 plots an example of skipper image resolution as a function of the number of skips. The dashed line corresponds to the expected analytical trend as given by Equation 4.1. Red points are measurements of the resolution for increasing number of skips, from 1 to 1000. Data follow the expected behavior. Individual electron peaks are gradually resolved by increasing the number of skips. This evolution is visible in Figure 4.5. With skipper CCDs, the ADUelectron calibration constant can be easily extracted when individual electrons are resolved. It is sufficient to measure the distance between the centroids of two single-electron peaks; typically the 0and the 1-e -(those with higher

Figure 4 . 5 :

 45 Figure 4.5: Pixel charge distribution for 1, 100, and 3000 skips. Single electron peaks start being visible at 100 skips. At 3000 skips the resolution equals 7% e - and individual electrons are fully resolved.

Figure 4 . 6

 46 shows the location of LSM facilities with respect to the Fréjus peak and the tunnel access points. The rock overburden in correspondence of the LSM site amounts to 1.7 km (4800 m water equivalent). The measured muon flux on site is 5.4 m -2 d -1 [142]. This value is ∼20× higher than SNOLAB, however, it is still quite low compared to sea level (∼200 m -2 s -1 ). The overall neutron flux ranges between ∼40 and

Figure 4 . 6 :

 46 Figure 4.6: Illustration of the LSM location. The lab facilities are located midway through the Fréjus tunnel, a few hundreds of meters away from the French-Italian border.

Figure 4 . 7 :

 47 Figure 4.7: Illustration of DAMIC-M apparatus. The CCD stack lies in an electroformed copper cryostat shielded in a copper box for IR. The detectors are cooled down using liquid nitrogen (LN2). The first layer of shielding is an inner ancient lead castle (∼5 cm). This is surrounded by few tens of cm's of low-activity lead and ∼50 cm cylindrical polyethylene castle.

Figure 4 . 8 :

 48 Figure 4.8: Preliminary design of the DAMIC-M cryostat. The vertical CCD stack is located at the bottom of the cryostat. Kapton cables running along the entire cryostat geometry are also shown.

  sure with O(0.1 dru) background rates. Achieving the desired exposure scale ultimately comes down to accumulating sufficient detector mass (and ensur-ing stability over data acquisition periods). It is therefore critical to have a satisfactory production yield of science-grade skipper CCDs. Factors such as fabrication protocols, CCD format, probing and packaging procedures are studied in advance to inform the definitive design and process flow. Preproduction batches of skipper CCDs are being tested extensively for the purpose. As a result, certain parameters have already been defined: e.g., the final CCD format (6k × 1.5k). Some others are under study: e.g., the wafer backside processing (see Section 4.2.1). In terms of background goals, important expertise was acquired with DAMIC at SNOLAB and the construction of its background model seen in Chapter 3. Broadly speaking, DAMIC-M foresee an order of magnitude rate reduction solely from the deployment of lowcontamination materials and adjustments on detector parts fabrication/handling. Improved detector design, background rejection and possibly fiducial cuts on CCD data will push the bar further down towards the dru fraction. Section 4.2 details the research and development efforts towards DAMIC-M science goals, focusing on the CCD testing activities and the background mitigation measures. Some space is also devoted to the development of novel electronics for even lower noise and faster readout (with a consequent improvement on the readout-dark current trade off). One kilogram-year of data with O(0.1 dru) overall backgrounds will achieve DAMIC-M leading sensitivities to light WIMPs and hidden sector particles. DAMIC-M sensitivity projections for these candidates are presented in Figures 4.9 and 4.10, along with upper limits from other leading experiments in

ure 4 .

 4 [START_REF] Vera | Rotation of the Andromeda Nebula from a Spectroscopic Survey of Emission Regions[END_REF] show projections for light mediator (top) and heavy mediator (bottom) hidden sector dark matter. In the heavy mediator case, the thick solid lines in yellow and orange correspond to the expected cross sections (based on relic abundance measurements) for scalar and fermion candidates, respectively.

Figure 4 . 9 :

 49 Figure 4.9: DAMIC-M sensitivity projections for spin-independent WIMP-nucleus scattering (top) for nuclear recoil (dashed) and accompanying Migdal electrons (dotted) signals, and hidden-photon kinetic mixing parameter (bottom).

Figure 4 . 10 :

 410 Figure 4.10: DAMIC-M sensitivity projections for light mediator (top) hidden sector and heavy mediator (bottom) hidden sector dark matter. Heavy mediator case: the labeled thick solid lines in yellow and orange correspond to the expected cross sections for a scalar and fermion candidate, respectively. Light mediator case: the labeled thick solid line in yellow represents the expected cross sections for a freeze-in produced candidate.

Figure 4 . 11 :

 411 Figure 4.11: Portion of highly defective CCD image from a DAMIC-M pre-production batch.

Figure 4 . 12 :

 412 Figure 4.12: DAMIC-M production CCDs fabrication process flow. Companies/locations and images representative of the manufacturing stage are reported on the right-hand and left-hand sides of the process, respectively.

Figure 4 . 13 :

 413 Figure 4.13: DAMIC-M pre-production wafer diced in four 6k × 1.5k

Figure 4 . 14 :

 414 Figure 4.14: Defects in four CCDs diced from a single pre-production wafer.

Figure 4 .

 4 Figure 4.14 shows results from CCDs of the same wafer framed accordingly to their origin in the wafer. All CCDs feature important defects, with the third from the top being almost completely saturated with charge. The presence of these defects has been investigated in a variety of ways. Some of the wafers

Figure 4 . 15 :

 415 Figure 4.15: Evolution of defects in a PP1 CCD as a function of the substrate voltage

  Cosmic flux is an increasing function of altitude. DAMIC-M CCDs (and other detector materials) are always transported at sea-level on transatlantic shipments. No shipment occurs via airplane. During idle periods, detectors are stored underground whenever possible. In particular, after ingot production in Denmark, DAMIC-M silicon is stored 1.1 km underground, at Boulby lab (UK), awaiting for slicing at SEHE. A transatlantic cargo ship then carries wafer lots to SNOLAB, where cosmic activation is practically null. Pre-production and production wafers go to DALSA from SNOLAB. As of now, about 200 DAMIC-M wafers (i.e. 800 potential CCDs) are stored deep underground in Sudbury. During stor-

Figure 4 . 16 :

 416 Figure 4.16: Fifteen-ton iron castle used for DAMIC-M wafers transatlantic shipment.

Figure 4 . 17 :

 417 Figure 4.17: Prototype of DAMIC-M electroformed copper box grown and machined at Canfranc underground laboratory.

Figure 4 .

 4 Figure 4.17 shows a prototype EFCu CCD box fabricated at LSC. Different materials are also being considered for the signal flex cable: Kapton and Axon [156]. Both options are being assayed and their contributions simulated with GEANT4 in order to make an informed decision.

Figure 4 . 18 :

 418 Figure 4.18: Initial (top) and final (bottom) DAMIC-M detector design.

Figure 4 . 19 :

 419 Figure 4.19: The latest DAMIC-M CCD stack (top) and module (bottom) design.

  file. The readout part will feature programmable integration time constants and gain while maintaining correlated double sampling capabilities and increasing the pixel value saturation threshold. Essentially, the DAMIC-M electronics will consist of: a clock and bias sequencer board, a near-sensor differential CCD amplifier (DCA), a fast 18-Bit 15 Msps analog-to-digital converter (ADC), and the Online Digital Interface for Low Noise Electronics (ODILE) motherboard equipped with a field-programmable gate array (FPGA) for timing and overall control.

Figure 4 .Figure 4 . 20 :

 4420 Figure 4.20: Simplified schematics of DAMIC-M electronics chain. Programmable logic is shown in maroon. Mezzanine boards are shown in green. Cold components are shown in gray, inside the cryostat shown in blue.Adapted from[START_REF] Thomas | Cameras in the Dark: Direct Detection of Dark Matter with Charge-Coupled Devices[END_REF].

Figure 5 . 1 :

 51 Figure 5.1: DAMIC-M LPNHE cleanroom. Three test setups were present at the time of the picture, two of which operational (orange and blue) . Some of the control/readout electronics (electronic boards, power supplies, etc.) used in these test-chambers can be seen next to the orange cryostat. A lightblue ESD-safe mat can be seen next to the silver cryostat.

Figure 5 . 2 :

 52 Figure 5.2: Assembled blue cryostat. Plates are attached to the cubic base frame. The door-plate can be sealed by means of screw-handles at its edges.

Figure 5 . 2 shows

 52 the cryostat after assembly. Plates were screwed to the frame following a star-like pattern and using a torque gauge wrench to not exceed maximum allowed value 70 inch-lb. O-rings were fit into plates grooves to ensure proper sealing. Plates carrying ports for instrumentation interface (e.g., electronic feedthroughs, vacuum pump, etc.) were assembled according to a specific disposition in view of the test chamber installation on a customized shelving unit designed by LPNHE engineers (see later figures). A front door-plate was installed to access the cryostat. A relief valve used to break vacuum is located on a KF-16 (NW-16) port on the right plate (not visible in Figure 5.2). The same plate hosts six more ports: 1× KF-50, 2× KF-40, 2× KF-25 and one further KF-16. The bottom plate hosts a CF 2.75 inch port to accommodate the cryocooler cold head. Left and top plates LF ISO63 ports both host two electrical D-Sub 50-pin feedthroughs for test system air-side electronics. The back plate has no ports, it would later be exchanged with another plate carrying cooling pipes for use with liquid nitrogen.

Figure 5 . 3 : 1 5 . 3 .

 53153 Figure 5.3: Top: CCD copper support and RTD (far) and resistor (near) aluminum holders attached to its bottom. Bottom Left: CryoTelGT copper cold head coming through the cryostat port. A germanium RTD monitors the cold head temperature. Bottom Right: Copper support screwed to the cooler cold head. Wires deliver electrical current to 25 Ω and 50 Ω resistors.

Figure 5 . 4 :

 54 Figure 5.4: External elements of the blue-cryostat test system cryogenics: cryostat, vacuum pump, pressure gauges, and cryocooler

Figure 5 . 5 :

 55 Figure 5.5: Pressure evolution inside the blue test chamber as measured by the cryostat pressure gauge in hPa (1 hPa=1 mbar). Cryocooler cold head temperature is reported as well, in kelvins.

Figure 5 . 6 :

 56 Figure 5.6: UW1612S in its aluminum box screwed to the copper support inside the cryostat. A RTD holder is attached to the box using Kapton tape and vacuum grease. The holder carries a PT-102 temperature sensor.

  Second-stage PCB shaping clock signals provided by the controller and amplifying the CCD video signal • Breakout PCB distributing clock, bias and video lines over different connectors • Power supplies (PS) for the controller bias board, the second stage amplification and the CCD substrate voltage. The CCD controller is produced by Astronomical Research Cameras (ARC) [166] and is referred to as Leach [167]. The Leach comprises a number of PCBs to supply bias and clock signals to the CCD according to a user-defined sequencer, and process/digitize outputs from CCD video channels. The boards are located inside a housing crate containing the controller backplane and an ARC-73 power control board. The crate is supplied with DC power using the ARC-80 supply. Four PCBs are installed in the housing. The ARC-22 fiber optic timing board executes communication between controller and host computer, generates timing waveforms and provides overall supervision. The ARC-32 clock driver board converts digital clock signals into their analog counterparts. The LBNL-designed ARC-33 bias board provides the necessary DC bias voltages, requiring an external power supply of -30 V. The ARC-45 video board does the processing and digitization of video outputs from two CCD video channels. The system is administrated with a host computer where an ARC-66 PCIe board is installed. Communication between computer and controller is achieved using fiber optic cables. The Leach sends (receives) clocks and biases (video output) to (from) the air-side breakout and second stage PCBs designed at UW. The breakout board is used to route clock, bias and video signals in and out the second stage board, where these are shaped and amplified, respectively. The breakout board has no active components since it only gathers and conveys the signals. It features the following D-Sub connectors: 1× 37-pin male (to clock board), 1× 25-pin female (to bias board), 2× 15-pin male (to video board) and 1× 50-pin female (to second stage board).

Figure 5 . 7 : 5 . 8 .

 5758 Figure 5.7: Top: Leach controller and external power supplies. Skipper video traces are visible in the oscilloscope. Bottom: Second stage and breakout boards. Connectors are labeled according to the signals they convey.

Figure 5 . 8 :

 58 Figure 5.8: Simplified schematics of the blue-cryostat test system air-side electronics. Left to right: An ARC-66 PCIe board is installed in the host computer to operate the CCD controller. On the Leach-end, the timing board (ARC-22) manages clock, video and bias boards (ARC-32, -45, -33, respectively). The boards send (receive) clock and bias (video) signals to (from) the breakout board, where they are conveyed on to the second stage board through a 50-pin connection. The second-stage board shapes clocks and amplifies the CCD video signal. A 50-pin feedthrough on the cryostat enables airvacuum sides transition. The chain continues inside the chamber with a 50-pin Kapton flex cable connecting to the CCD (see Section 5.1.3).

Figure 5 . 9

 59 Figure 5.9 reports examples of clock oscilloscope traces during these tests. A vertical and horizontal clock and the summing well pulse are shown. Measured values are consistent with configuration file selections. The pin outputs of clock and bias boards were all validated in this fashion.

Figure 5 . 9 :

 59 Figure 5.9: Top to bottom: Vertical, horizontal and summing well clocks oscilloscope traces. Amplitudes and widths are reported (rounded) as measured with the oscilloscope. Measured values are consistent with configuration file selections.

Figure 5 . 10 :Figure 5 . 11 .

 510511 Figure 5.10: Vertical clock of Figure 5.9 after RC-shaping in the second-stage board.

Figure 5 . 11 :

 511 Figure 5.11: Setup used to test video lines. A sinusoidal pulse is injected into the video pins at the CCD-end of the flex. A gain of 32 is observed at the Leach end of the chain. The second stage board connected to the cryostat feedthrough can be seen in the left-hand side figure.

Figure 5 . 12 :

 512 Figure 5.12: UW1616S in its aluminum package, sitting on ESD-safe bag and box. CCD flex connector is shorted to prevent stray electrostatic charge to seep in.

Figure 5 . 13 :

 513 Figure 5.13: Top: UW1612S installed in the blue-cryostat test chamber. Bottom: bluecryostat setup during commissioning. External electronics and cryostat are visible on upper and lower shelves, respectively.

Figure 5 . 14 :

 514 Figure 5.14: Substrate voltage evolution at CCD start up. An erase procedure is performed few seconds after applying clocks and biases. Used ramp-down and ramp-up rate is 15 V/s. Parallel clocks are set to 10 V during erase.

Figure 5 . 15 :

 515 Figure 5.15: Slow control package schematics. Slaves represent machines containingthe (or a copy of) database. Only the primary slave containing the master database pertains to the blue-cryostat test system. Taken from[START_REF] Nikkel | Astro-slow-control user manual[END_REF].

Figure 5 . 16 :

 516 Figure 5.16: Blue-cryostat test system private internal network. Elements outside the network are shown as well for completeness. Power refers to LPNHE power grid. UPS is the APC SMC1000 uninterrupted power supply. PDU is the power distribution unit used to control pump switch. The TPS compact vacuum pump is connected to the SC machine using a serial RS-232 port, enabling monitoring of pump parameters (e.g. rotation speed) and pump-end pressure gauge. TPG362 is the Pfeiffer pressure controller managing the PKR251 gauge.

Figure 5 . 17 :

 517 Figure 5.17: Example of alarm management box in the slow control web interface. An alarm is issued when reject temperature is greater than 50 • C.

  oscilloscope accessible remotely. Skipper video traces during readout or idle mode look as shown in Figure 5.18. Their features are described in the caption. Trace structure depends on waveform file and CCD parameters, but should always feature the shown elements, if the readout amplifier works well. When clock signals and bias voltages do not fulfil specific constraints, traces will look distorted, and parameters should be optimized to achieve correct transfer and/or readout.

Figure 5 . 18 :

 518 Figure 5.18: Skipper readout video trace. Three NDCMs are shown. Trace elements are labeled. One NDCM starts with a reset pulse to set the reference voltage. The pedestal is then measured for an integration period t int . Afterwards, charge moves from summing well to sense node (SWHi pulse) and is integrated for t int . The output gate is finally pulsed low (OGLo pulse) to let charge back into SW.

Figure 5 . 19 :

 519 Figure 5.19: Example of DS9 analysis capabilities. The pixel area inside the green circle is characterized. Next to it, a muon track crossing the CCD from top to bottom can be seen.

•

  Multiskip image reconstruction • Noise characterization • Skip charge loss check • Charge calibration and dark current measurement • Fourier analysis.Skipper fits files come in the form of two-dimensional matrices of size N axis-1 × N axis-2 , where N axis-1 = N rows and N axis-2 = N columns • N skips . In particular, the first NDCM is followed (column-wise) by all other NDCMs of the same pixel before moving on to the next one. Data must be transformed from this format into a set of N skips single-skip images: one for each skip. Numpy 2D matrices are constructed starting from one multiskip image. CCDTesting stores selected ones into a multiple-extension fits file: the first three (from first to third NDCM), a user-chosen and the last skip images, the average image of all skips, the standard deviation image of all skips and the difference images between first and second, and second and last skips. These can be accessed by user for visual inspection. Images can also be plotted in theCCDTesting L A T E X report.Electronic noise is characterized by locating and fitting a Gaussian to the 0-electron peak. This strategy is used for dark rates < 1 e -/pixel, when the 0-electron bin dominates. The fit is performed in the m 0e -± 2s 0e -range, where m 0e -and s 0e -are numerical estimates of peak centroid and standard deviation. Fit extracts parameters µ 0e -and σ 0e -, Gaussian mean and standard deviation, respectively. This procedure is carried out for incrementally averaged images from skip 1 to [10, 100, 200, ..., N skips ]. In this manner, it is possible to extract the resolution trend as a function of N skips , and assess its decrease as 1/ N skips . Single-skip and multiskip average image PVDs and resolution trend are reported in the CCDTesting report. Examples of these plots are shown in Figure 5.20. The reported values of noise are estimated as

Figure 5 . 20 :Figure 5 . 21 :

 520521 Figure 5.20: Top (two plots): Single-skip and 1000-skip PVDs. Fit curves to the 0e - peak are reported along with values of σ 0e -and estimated electronic noise. Note that in this case the Leach was operated in inverse charge-ADU mode. Bottom: measured noise (red points) compared to theoretical trend (dashed line). Data and model are compatible. The 100-skip point represents a fit misestimation of the resolution due to yet unresolved single electron peaks.

  named CTI significance and is used to check for skip CTI. The discrimination efficiency of S k was studied using a toy Monte Carlo approach. A selection cut of |S k | = 3 was first found empirically. Monte Carlo simulations then confirmed a discrimination efficiency of 100% and a negligible false positive rate for CTI=10 -3 in 1100 × 10 1000-skip images. These simulations were carried out assuming highly populated images (50% charged pixels) representative of shallow-depth operation. The first-second PVDD plot associated to skipper image of Figure 5.21 is shown in Figure 5.22. A significance S k < -15 indicates important skip charge loss as confirmed by visual inspection. Selection cuts on S k proved to be an effective tool to discriminate charge loss in skipper images. However, given the S k dependence on various operating parameters (image size, population, number of skips), cuts have to be optimized for specific situations. Observed and expected tail entries and their ratio are simple robust quantities, also monitored to check for skip CTI.

Figure 5 . 22 :

 522 Figure 5.22: First-second pixel value difference distribution. Charge loss is manifest as a prominent lower-tail in the otherwise Gaussian PVDD. Reported values of the CTI coefficient and significance indicate important charge loss.

Figure 5 . 23 :

 523 Figure 5.23: Dark current Gauss-Poisson convolution fit of 0e -and 1e -electron peaks. Convolution fit (CF) and anticlustering (AC) estimates are reported in title. They are consistent within uncertainties.

Figure 5 . 24 :

 524 Figure 5.24: Full image skip fast Fourier transform produced with CCDTesting. The wide peaked structure slightly above 5 kHz was observed in both blue and orange test chambers and is thus likely to come from a shared component or connection within the lab.

Figure 5 . 25 :

 525 Figure 5.25: Top to bottom: amplifier gain, single-skip noise and average image noise as functions of the integration time. In bottom plots, the green line represents noise before calibration (in ADU units), the red solid line represents noise post-calibration. The latter is to be considered for optimization purposes.

Figure 5 . 26 :

 526 Figure 5.26: Average image pixel value distributions compared at the threshold between V drain and summing well. Lowering V drain by 1 V brings dark current back to nominal levels. PVD fit fails in the top case due to very high dark current.

  Low Background Chamber (LBC) is the DAMIC-M prototype experiment at the Modane underground laboratory. The detector features two 6144 × 4128 science-grade skipper CCDs, for an overall sensitive mass of 17.8 g. These characteristics and its low background rates ( 10 dru) make for a competitive dark matter experiment. The LBC is a demonstrator and a test bench for DAMIC-M. Its setup is frequently upgraded to accommodate and test parts and technologies to be deployed in the final experiment. Installation and commissioning occurred between October 2021 and March 2022, with extensive CCD characterization activities taking place in January and February. Science data acquisition runs have been ongoing for the last few months. The first DAMIC-M dark matter science result obtained with the LBC will be discussed in Chapter 7. The present chapter is subdivided into two sections devoted to apparatus and detector characterization. Section 6.1 provides a comprehensive description of the LBC apparatus, following the structure proposed for the blue cryostat test chamber in Chapter 5. LBC remote control capabilities and safety measures are also discussed. Section 6.2 delves into the CCD testing activities conducted to characterize and optimize UW6414D and UW6415D 1 operational parameters in view of the aforementioned science runs. The latter are discussed in Chapter 7, since further CCD parameter and data format optimization was conducted in the context of first unblinded analyses.

  Laminaire [159] and finalized during spring 2021. The room is subdivided into two spaces: an ISO class 6 4.2 m × 1.4 m gowning room and an ISO class 5 4.2 m × 4.7 m detector room. The amount of particulate inside the room is limited through HEPA filtering units and continuous airflow at a roughly constant speed of 0.2 m/s. A retractable roof opening is located in correspondence of the detector room to facilitate access for unwieldy instrumentation. Users first gain access to the gowning room. Head-the damic-m low background chamber covers, face masks and shoecovers are available in dedicated PPE boxes at the entrance. These items are worn in the above order while standing on a sticky mat. A shelving unit dedicated to personal protective equipment and cleaning solutions and a clothing rack are located midway across. Users wear powder-free nitrile gloves and subsequently a coverall suit, before heading towards a stainless steel bench located in proximity of the door to the detector room. Last PPE items are worn sitting: Tyvek bootcovers and a second pair of gloves, avoiding all contact with materials preceding the bench. The detector room door only opens when the gowning room door is closed (and vice versa). A second sticky mat is placed right in front of it, on the gowning room side. The cleanroom additionally features a passthrough chamber connecting gowning and detector rooms to transfer small size objects. Objects moving to the detector room are cleaned with IPA and lint-free wipes before placing them inside the passthrough. Clean room planimetry and configuration are illustrated in Figure6.1, along with location inside LSM. All items are shown according to the current disposition. The LBC apparatus rests in the detector room, in front of the door, midway across relative to the far "Italy" wall. The apparatus is supported by an aluminum-stainless steel mechanical structure designed to dislocate the far half (relative to the tunnel wall) of polyethylene (white crown) and lead (gray crown) shieldings and give access to the copper cryostat (light brown circle). Cryocooler (blue cylinder) and vacuum pump (red trapezoid) are accommodated on the support structure as well. A dedicated shelving unit located in between the apparatus and the Italy wall hosts cryogenic controllers and supply/control electronics. On the opposite side of the room (at the corner between Italy and SuperNEMO walls), slow control and DAQ machines are placed on a clean room grade table. Next to it rests a stainless steel workstation where maintenance operations are conducted. This additionally features a lower shelf about 10 cm above the ground, where polyethylene boxes containing tools and spare parts are stacked. CCDs are handled on a table near the "French" wall, equipped with ESD-safe mat and wrist strap. ESD-safe chairs and stools are available in the detector room.

Figure 6 . 1 :

 61 Figure 6.1: DAMIC-M clean room planimetry and location inside Laboratoire Souterrain de Modane. A top-view illustration of detector (left) and gowning (right) rooms is shown. Current instrumentation arrangement is reported (not to scale). The black rectangle represents a clean room pillar. Wall thickness is neglected for simplicity. Reported room sizes refer to internal dimensions. Illustrated instrumentation and tools are described in the text. The SuperNEMO experiment is currently under construction near DAMIC-M clean room. LSM rendering shows previous experiment NEMO apparatus.

  heat sealer and shipped to LSM. Parts shipped from other institutions were taken care of in a similar manner. Shielding and cryostat parts were cleaned at LPSC Grenoble in a ISO class 7 clean room. The polyethylene shielding was produced by Abaqueplast [177] and cleaned using high-purity ethanol and lint-free cleanroom grade wipes. External (internal) shielding lead components were machined at LEMER [178] (Fonderie de Gentilly [179]) and cleaned according to the following procedures. External parts were cleaned with highpurity ethanol and triple-bagged. Ancient/low-background internal lead underwent more sophisticate cleaning. Parts were initially scrubbed in a bath of acetic acid (CH 3 COOH) for about 10 minutes to remove any oxidation layers. After rinse in >18 MΩ ultra-pure water, they were further scrubbed for about 10 minutes in a 2 : 3 : 95 etching solution of nitric acid (HNO 3 ), hydrogen peroxide (H 2 O 2 ) and >18 MΩ water, respectively. Etching removes primordial-chain surface backgrounds accumulated during fabrication and storage. Parts were finally rinsed in >18 MΩ water, dried, and triple-bagged for shipment. Copper parts were cleaned as follows. Etching was performed submerging parts into a 1 : 3 : 96 mixture of sulfuric acid (H 2 SO 4 ), hydrogen peroxide (H 2 O 2 ) and >18 MΩ water. The solution was stirred for about 10 minutes. Figure 6.2 shows the copper cryostat top part submerged into the sulfuric acid solution during etching. After rinse in >18 MΩ water, passivation

Figure 6 . 2 :

 62 Figure 6.2: Copper cryostat (top part) etching in sulfuric acid solution at LPSC. The chemical reaction between copper oxide and sulfuric acid produces water and soluble copper sulphate, which gives the solution its blue color.

Figure 6 . 3

 63 shows a view of the support structure during assembly. The LBC external shielding design was validated with GEANT4 simulations on environmental neutrons and gammas. The total contribution was found to be sufficiently small for the LBC background budget (< 3 dru). The cryostat is laterally surrounded by (rests below) 150 mm (150 mm) of lead and 210 mm (200 mm) of polyethylene. At the stand height (below the cryostat) lateral shielding thins to 50 mm of lead and 150 mm of polyethylene. Finally, 50 mm of polyethylene separate cryostat from below external environment. Figure6.4 shows fixed parts of external shielding and support structure, and mobile assembly carrying cryostat stand (not shown), lower shielding closing parts and cryocooler (not shown). All shielding dimensions are reported. Support structure and external shielding were constructed in about a week. However, the structure was found to be exceedingly difficult to open and close when all the shielding was loaded, with its mobile parts prone to derailment. The upper external shielding was thus disassembled to be mounted at the end of the installation campaign, on a closed structure. The

Figure 6 . 3 :

 63 Figure 6.3: Closed LBC support structure. Salient elements are labeled.

Figure 6 . 4 :

 64 Figure 6.4: Rendering of LBC external shielding on support structure. Fixed parts of shielding and support structure are shown on the right. The mobile support hosting lower shielding, cryostat stand (not shown), pump and cryocooler (not shown) is illustrated on the left. Different parts are colored according to legend. Size of shielding parts reported in mm units.

Figure 6 . 5 :

 65 Figure 6.5: Left: LBC cryostat after manufacture. The vessel rests upside down relative to its arrangement in the LBC. The bottom part features one vertical and four lateral cross-oriented openings for ports and feedthroughs. Right: Cryostat mechanical drawing with dimensions in mm (side view).

Figure 6 . 7 :

 67 Figure 6.7: Cold hand and internal shielding installation. Ancient lead parts are labeled. A: Cold hand and fingers mounted on cold arm. Underlying extension cables (and two-to-one boards at flange) are installed before cold hand. B: 20 mm thick lead slabs stacked above cold hand. Short (26 mm) Teflon pillars prevent thermal contact. C: Lead castle construction around cold assembly. D: Complete lead castle. Capped flex cable passthroughs show next to copper fingers. All lead tops and caps are ancient.

Figure 6 . 8 :

 68 Figure 6.8: Installation of upper inner lead disks inside the top part of the LBC cryostat. The lowermost disk has a composite structure, consisting of a central 20 mm thick Roman lead disk and a 27.5 mm thick low-background lead centering ring.

Figure 6 . 9 :

 69 Figure 6.9: Left: Pump-end of the vacuum chain. Right: Author closing the LBC cryostat with hydraulic crane. Temperature control feedthrough is visible at the cryostat bottom part.

. 10 .

 10 In the LBC chain, an airside breakout board conveys all signals and included power supplies. A 3m-long cable connects it to the 50-pin cryostat feedthrough. On the vacuum-side, two-to-one boards split the CCD control signals into two sets destined to same-side readout stages (conventionally known as L and U) on opposite serial registers. Four vacuum-side amplifier boards amplify (shape) video (control) signals coming from (to) the CCDs. The differences characterizing the LBC electronics chain are explained as follows. CCD video signals are of µV/e -order and can pick up significant noise on their way to the amplifier. However, the same contributions become proportionally smaller post-amplification and signals can travel longer distances. Amplifier boards are located in proximity with the LBC CCDs. Airside

Figure 6 . 10 :Figure 6 . 11 :

 610611 Figure 6.10: Schematics of LBC electronics for one CCD. Left to right: all equipment before breakout board is the same as LPNHE blue cryostat setup. A single power supply (Keysight E36312A [185]) for bias and amplifier boards is used. The breakout board conveys all signals, including power supplies. The 3m-long signal cable connects breakout PCB to cryostat feedthrough. On the vacuum-side, signals are split by two-to-one boards (one per CCD) among CCD L and U readout stages. Split signals are shaped/amplified by vacuum-side PCBs directly connected to the detectors.

Figure 6 .

 6 Figure 6.11 shows CCD transfer setup (left) and 6417 installed in the LBC copper box bottom lot (right). The transfer proceeds as follows. In order to unpackage the CCD from the aluminum box, flex cables are fixed in place with Kapton and the box lid is removed. Unscrewing T-bars at package frame leaves the CCD free to move. The CCD is transferred to the LBC box with no lid and T-bars. One flex is taped back in place. Correct alignment is achieved by superposing dedicated holes on cable and box. The second flex is thus secured to mat. Copper T-bars are installed with care to preserve alignment.This last step determines thermal efficiency: it is crucial to supply sufficient pressure, yet not overtighten due to risk of flex damage or mechanical stress.Copper box with 6417 was installed on the LBC cold fingers. After reaching desired cryogenic conditions, CCD was started up. Detector performance was found generally compatible with results of preliminary testing conducted at the University of Washington. However, a quite high time-dependent dark rate was initially measured. This pointed at thermal inefficiency, since no other physical effect was expected to produce the observed spatially uniform charge distribution. After further checks, and in particular the observation of a weak dependence on temperature, LBC was open and CCD box removed for inspection. Extension flex cables were judged to be insufficiently secured by T-bars. This was probably exacerbated by thermal contraction at low tem-

Figure 6 . 12 :

 612 Figure 6.12: Top: CCD box installed on cold copper fingers. Vacuum-side amplifier boards are also visible on external walls of lead shielding. Bottom: 6414 (top device) and 6415 (bottom device) science-grade skipper CCDs installed in the LBC copper box.

2

 2 and the DAMIC-M DAQ are used. The DAMIC-M central DAQ is developed at Centro Atómico Bariloche, Argentina. It makes use of the MQTT broker as a central message dispatcher [186], as opposed to the basic user-controller-CCD communication flow.

Figure 6 . 13 :

 613 Figure 6.13: Low Background Chamber slow control/DAQ/power network. The LSM UPS is connected to power grid. An additional UPS (DAMIC-M UPS) extends overall runtime in case of power outage.

  Figure 6.14 shows LBC slow control and DAQ machines (left) and cryogenic/DAQ instrumentation (right).

Figure 6 . 14 :

 614 Figure 6.14: Low Background Chamber slow control and DAQ machines (left) and cryogenic/DAQ instrumentation (right).

Figure 6 . 15 :

 615 Figure 6.15: Left: The DAMIC-M Low Background Chamber without external shielding in December 2021. Right: The DAMIC-M Low Background Chamber with full shielding in March 2022.

Figure 6 .

 6 [START_REF] Green | Dark Matter in Astrophysics/Cosmology[END_REF] shows LBC as operated between December and March (left) and after external shielding installation in March (right).

Figure 6 .Figure 6 . 16 :

 6616 Figure 6.16 shows the Fast Fourier Transform of two single-skip images acquired with and without said connection. A dominant noise contribution across the entire frequency spectrum can be seen. After further investigation,

Figure 6 . 18 :

 618 Figure 6.18: FFT of 6414 multiskip images taken with DAQ1 only (teal) and both (red). Significant noise contributions after DAQ2 installation are apparent. Mismatch between peaks around 5 kHz is explained in the text.

Figure 6 .

 6 [START_REF] Clowe | A Direct Empirical Proof of the Existence of Dark Matter[END_REF] shows average image pixel value distributions for two 650-skip images taken with CCD 6414. SW width is 0.48 µs for both CCDs in the top case. Value changes to 0.8 µs for 6415 only in the bottom case. No pedestal subtraction is done on these images. Similar behaviour is observed for 6415. The effect translates to low-frequency ( 10 Hz) noise components affecting image pedestal on a row basis. This is shown in subfigures on the right-hand side, which report portions of the corresponding images. Given fast timescales characterizing readout clocks, it could rather be related to periodic overlap of the two signals, expected to occur on a much longer timescale. Note that the effect was observed for combinations of equal values (0.48 µs and 0.8 µs) which do not affect performance when set independently for either CCD. Further investigations were not conducted, the goal being parallel operation preserving data quality. Optimal parameters were set taking into account noise, CTI and dark current rates (see Section 6.2.2). Values of 0.24 µs and 0.4 µs were ultimately used for 6415 and 6414 summing well widths, respectively.

Figure 6 . 19 :

 619 Figure 6.19: CCD 6414 average image PVDs for equal (top) and different (bottom) summing well widths. Gaussian best-fit curves are also shown. No pedestal-subtraction is done on these images. Side figures show noiseonly fractions of the corresponding image. Significant row baseline shift is visible in the top case. No such effect is seen in the bottom.

Figure 6 . 20 :

 620 Figure 6.20: Mirror pixel value map for single skip image acquired with 6415 L and U amplifiers. Values are pedestal subtracted. High correlation between mirror pixels is evident.

. 21 .

 21 Proposed plots report dark current as a function of image exposure in 6415 L and U amplifiers (top and bottom plots, respectively), in two regions of the exposed area. Each amplifier would read out one half of the physical serial register plus 128 overscan pixels: 3200 columns in total. The two analyzed regions comprise the 1024 closest (column 1 to 1024) and farthest (column 2048 to 3072) columns from the amplifier. Measurements are fitted with lines to extract dark current rate and clock-induced charge. Line offset and slope correspond to clock-induced charge and dark current, respectively. Expressed in common units, dark current is 4 -6 × 10 -3 e -/pixel/d for three of the four measurements. Rate is one order of magnitude higher (∼6 × 10 -2 e -/pixel/d) in the 1024 columns closest to the U amplifier. Given spatial and time dependence, amplifier glowing is the most likely explanation. Figure6.22 shows the charge profile as a function of column number. The corresponding image was acquired with ×10 serial binning. Both amplifiers feature a number of hot (binned) columns (high N pixels per column). These would be masked at the analysis stage. A steep rise in charged pixels around column 460 marks the beginning of glowing un-

Figure 6 . 21 :

 621 Figure 6.21: CCD 6415 dark current as a function of exposure for L (top) and U (bottom) amplifiers. Measurements are performed in 1024 columns regions closest and farthest from amplifiers. Labeling is reported in the legend. Data uncertainties are estimated in the Gauss-Poisson convolution fit. Line offset and slope measure time-independent and -dependent contributions, respectively. Clusters or CTI are not masked in this analysis.

Figure 6 . 22 :

 622 Figure 6.22: Charge column profile in 6415. Dashed black line separates L and U amplifiers column range. Prominent glowing in U amplifier is visible in column range 460-615 (column 615 pixels are closest to the readout transistor). Several hot columns can be seen for both amplifiers.

Figure 6 . 23 :Figure 6 . 24 :

 623624 Figure 6.23: Number of pixel events with q > 2e -as a function of N skips , for a nominal 1-day data run. Different values of single-skip noise are considered. Points encircled in red constitute minima for the different datasets. Optimal N skips value is sensitive to the initial assumption on single-skip noise.

  V) suppressed it. The modification also suppressed few neighboring hot columns, possibly because of decreased temperature in the corresponding regions. Dark current in identified glowing regions normalized to levels observed in the rest of the CCDs. Average images shown in Figure 6.25 zoom in on 6415 U amplifier region during first (top) and second (bottom) data runs. Run 2 was conducted after shielding installation, DAQ2 deployment and above change in settings. Highcharge pixels appear in yellow. U amplifier light (right-hand side) is apparent in top image. No luminescence excess is detected during the second data run (bottom). Dark current looks uniform across the column range. Data run 1 image features several high-energy clusters with vertically elongated topol-

Figure 6 . 25 :

 625 Figure 6.25: Comparison of 6415 average images in data runs 1 and 2. U amplifier region is zoomed in. Color scale is in electron units. High-energy clusters, transfer inefficiency and amplifier luminescence are suppressed in data run 2. See text for details.

  collaboration[188] was attempted during the second commissioning phase.Multiple erase procedures were carried out during a temperature cycle as shown in Figure6.26. Image format settings were modified to read 84 rows with a ×10 parallel binning, for a ten times faster readout. Data was acquired with a hybrid SIPC-CR strategy: six images (sixth in steady state) were acquired after an erase procedure and a CCD clear, in this order. These actions were looped through. Temperature was gradually ramped up from 130 K to 190 K, in steps of 10 K. It was then decreased back to 130 K. Set ramp rate was 0.1 K/min. The multi-erase loop ran throughout the entire temperature cycle. No improvement in dark current was observed at stoppage. One salient difference with respect to RADAC approach might explain this finding. CCDs 6414 and 6415 dark current had fully stabilized at the time of the procedure. On the other hand, RADAC perform it soon after start up. Dark current is always higher at switch-on, due to the hole release mechanism described in Section 5.1.3. At the LBC, few high-temperature erase procedures had been performed in the two devices (several) days prior to the multi-erase cycle. This

Figure 6 . 26 :

 626 Figure 6.26: Cold finger RTD measurement during multi-erase temperature cycle. The 1-hour multi-erase loop runs throughout the entire temperature cycle. Temperature is raised by 10 K at a time, with a ramp rate of 0.1 K.

Figure 7 . 1

 71 Figure 7.1 shows examples of dark matter electron scattering rates for heavy and ultra-light mediator candidates, for m χ = 10, 100 MeV produced with DamicMSignal (factor c -2 is hereon omitted from mass units for simplicity). Cross sections are set to produce approximately the same number of events in a kg-year exposure for m χ = 10 MeV and m χ = 100 MeV to facilitate comparison. In both cases, higher cross sections are required for 100 MeV

Figure 7 . 1 :

 71 Figure 7.1: Top: Heavy mediator differential rate for 10 MeV (teal) and 100 MeV (red) dark matter. Cross section values are adjusted to obtain the same number of events. Heavier particles produce higher energy signals. Bottom: Ultralight mediator differential rate for 10 MeV (teal) and 100 MeV (red) dark matter. Cross section values are adjusted to obtain the same number of events. Heavier particles produce higher energy signals.

Figure 7 . 2 :

 72 Figure 7.2: Charge differential rates for heavy mediator 10 MeV dark matter. Red (teal) histogram represents the rate obtained with pair-creation probabil-

2108 µm 2 b = 1 . 98 × 10 -4 µm - 1 α 1 ( 7 . 3 )

 2198101173 = 0.859[START_REF] Penzias | Free Hydrogen in the Pegasus I Cluster of Galaxies[END_REF] β = 6.7(4) × 10 -3 keV -where energy dependence parameter β leads to a difference in σ xy < 1% for a 10 eV variation at 10 eV. Edge losses caused by diffusion across the junction of regions read out by different amplifiers are not simulated. However, they are expected to concern < 0.001% of events and will cancel out since the phenomenon equally affects the two regions. If binning is foreseen during data acquisition, charge from N PBIN column pixels and/or N SBIN row pixels is cumulated in one binned pixel. Figure7.3 shows pixel charge distributions from detector response simulations pre-diffusion (red), post-diffusion (teal) and post-binning (black) for heavy mediator 10 MeV dark matter (same cross section as in Figure7.1). The net effect of diffusion is to increase the 1-e -bin content, as more pixels are populated with single electrons. Higher-charge bins are correspondingly depleted. Binning gathers diffused charge back up to an extent dependent on diffusion σ xy . With the present parameters, maximum diffusion is 4 pixels so that 10 × 10 binning can regroup all event carriers

Figure 7 . 3 :

 73 Figure 7.3: Charge diffusion and 10 × 10 binning PCDs. In pre-diffusion entries, charge is injected at a given spatial point in the CCD and ascribed to a single pixel. Post diffusion, event charge is redistributed over different pixels according to diffusion dynamics. Post-binning histogram is produced by cumulating charge from 100-pixel sized squares across the pixel area. Number of entries for the different histograms is reported in legend.

  lated as detector response; rather, they are encoded in the PCD model fitted to data and left as free parameters in the inference analysis. These characterize the essential background model used in this work. Signal models are produced for the 25 mass points (in MeV) given by the following line of code: np.concatenate([np.geomspace(0.53,0.9,10),np.geomspace(1,1000,15)]),

  Figure 7.6 shows an example of f(t σ |H 1 ) for m χ = 20 MeV. The distribution is well reproduced by a chi-square function with one degree of freedom. The corresponding asymptotic expression is thus used to extract sensitivity and upper limits, with p-value = 0.1 expected for t σ = 2.7055. The distribution f(t σ |H 0 ) does not fulfill Wilks theorem hypotheses since σ e = 0 lies on the boundary of the search parameter space. This is the reason why backgroundonly Monte Carlo datasets must be used to compute med{f(t σ |H 0 )}. e |H 1 ( e )) for a DM signal of 20 MeV 2 d.f.=1

Figure 7 . 6 :

 76 Figure 7.6: PLR distribution for Monte Carlo signal datasets, for 20 MeV heavy mediator dark matter. The distribution is well reproduced by a chi-square distribution with one degree of freedom.

Figure 7 . 7 :

 77 Figure 7.7: Profile likelihood ratio cross section scan on Monte Carlo backgroundonly dataset. The would-be upper limit gives a test statistic value of 2.7055 and coincides with σe = 1.2 × 10 -37 cm 2 . The test statistic converges to zero for decreasing cross section, as expected for backgroundonly datasets.

Data from runs 1

 1 to 3 was acquired in continuous readout mode. A 10 × 1 binning was used in the first two runs, then changed to 10 × 10 for run 3. A post-clean DAQ strategy and 10 × 10 binning are used for run 4 to reduce dark current and enhance sensitivity. For all runs, 640 = 6400/SBIN binned columns were acquired (320 per amplifier) covering the physical CCD and including additional 256 overscan (unbinned) pixels. Number of rows was set to 840 for the first three runs (840 = 8400/PBIN for run 3), and 110 = 1100/PBIN

Figure 7 . 8 :

 78 Figure 7.8: CCD 6414 L2 amplifier hot column mask. Note that by construction the mask removes columns with outlying low charge profile as well. First (prescan) and last 12 (overscan) columns are always masked.

7. 2 . 2

 22 DAQ StrategyDAQ strategy evolved based on preliminary results obtained with the first two science runs and sensitivity analyses conducted with DamicMSignal. Figure7.9 shows sensitivity forecast in the mass range[START_REF] Hubble | The Realm of the Nebulae. Mrs. Hepsa Ely Silliman[END_REF] 1000] MeV for different binning configurations, dark current and acquisition mode. As remarked previously, binning is expected to enhance sensitivity since it amounts to a rough hardware clustering with no corresponding background increase. This is the case when binning is implemented, but all other settings are maintained. Black (10 × 1), cyan (5 × 5) and purple (10 × 10) dashed lines show precisely this effect. The marginal difference in sensitivity between the latter two is explained considering that the majority of signal charge is gathered up when adopting a 5 × 5 configuration. For a fixed dark current, from that point on, noteworthy improvements can be obtained by acquiring more exposure (magenta dashed line). A post-clean image acquisition strategy translates to less electrons per bin, since the CCD is rid of charge right before an image is taken. Correspondingly, exposed pixels are discarded, so that a 2/f longer run is necessary to achieve the same overall exposure, with f the fraction of physical CCD read out in the new configuration. In order to sufficiently lower the mean number of charges per bin, a quarter image post-clean (QIPC) was opted for (∼1000 physical rows). Teal and red solid lines in Figure7.9 show

Figure 7 . 9 :

 79 Figure 7.9: LBC continuous readout and post-clean DAQ modes sensitivity forecasts. Different datasets are implied whenever exposure or dark current values are separated by a plus in legend. A joint-likelihood analysis is performed correspondingly (see Section 7.3).

Figure 7 .

 7 [START_REF] Vera | Rotation of the Andromeda Nebula from a Spectroscopic Survey of Emission Regions[END_REF] shows the dark current variation

Figure 7 . 10 :

 710 Figure 7.10: Dark current column dependence in CCD 6415 L2 amplifier.

  Profile likelihood over the e parameter Heavy Mediator, DM mass 20 MeVProfile likelihood Critical value for 90% UL Inferred value of the cross section UL

Figure 7 . 11 :Figure 7 . 12 :

 711712 Figure 7.11: PLR cross section scan on science run 3 data for m χ = 20 MeV heavy mediator dark matter. Corresponding upper limit is σe = 2.4 × 10 -37 cm 2 .PLR approaches zero (i.e. maximum likelihood) at 7.8 × 10 -38 cm 2 .

Figure 7 .

 7 Figure 7.12 shows CCD 6415 L2 amplifier columns [1, 150] data overlaid on full and signal-only models for heavy mediator dark matter. Data and full model are expectedly in partial agreement, with a reduced chi-square value of χ 2 /ndf = 2826.75/69. A single 4-e -count is visible, expected with a 15% probability. Note that the full model does not equal the sum of signal and background, instead being a convolution of the two. The following consideration can be made: in absence of dark current, the numbers of 1, 2 and 3 electron events would be much smaller than what observed. Dark current is the main pixel hit contributor.

2 ]

 2 Fr e e z e -i n DM-e scattering (F DM = ( m e /q) 2 )

Figure 7 . 13 :

 713 Figure 7.13: Top: DAMIC-M LBC heavy mediator dark matter-electron scattering cross section 90% C.L. exclusion limits. Bottom: DAMIC-M LBC ultralight mediator dark matter-electron scattering cross section 90% C.L. exclusion limits. Results from other dark matter experiments are shown for comparison[START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF][START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF][START_REF] Aprile | Light Dark Matter Search with Ionization Signals in XENON1T[END_REF][START_REF] Aprile | Emission of single and few electrons in XENON1T and limits on light dark matter[END_REF][START_REF] Cheng | Search for Light Dark Matter-Electron Scattering in the PandaX-II Experiment[END_REF][START_REF] Agnes | Search for dark matter particle interactions with electron final states with DarkSide-50[END_REF][START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF][START_REF] Arnaud | First Germanium-Based Constraints on Sub-MeV Dark Matter with the EDELWEISS Experiment[END_REF][START_REF] Agnese | Erratum: First Dark Matter Constraints from a Super-CDMS Single-Charge Sensitive Detector[END_REF]. Benchmark models taken from[START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF].

Figure 7 . 14 :

 714 Figure 7.14: Heavy (top) and ultra-light (bottom) mediator upper limits and sensitivity line with ±1σ and ±2σ uncertainty bands. In both cases, at high masses the limit deviates from the sensitivity by more than +2σ due to few 3-e -and one 4-e -counts.

Figure 1 . 1

 11 Figure 1.1 False color mosaic of the Coma cluster. Two large elliptical galaxies, NGC 4889 and NGC 4874, dominate the cluster's center. The mosaic combines visible-light data from the Sloan Digital Sky Survey (color coded blue) with infrared views (red and green, respectively) from NASA's Spitzer Space Telescope. Credits: NASA/JPL-Caltech/L. Jenkins (GSFC) . . . . . . . . . . . . . . . . . Figure 1.2 The spiral galaxy NGC2403 (left) and its rotation velocity profile (right). The profile is broken down in three mass components: gas, visible-spectrum matter (stars, etc.) and a non-luminous galactic halo component increasing with galactocentric distance. Credits: [13] (left) and [14] (right). . . . . . . . . . . . . . . . . . . . . . . . Figure 1.3 Collage showing six different galactic clusters collisions taken with Hubble Space Telescope (HST) and Chandra X-ray Observatory. The post-collision distribution of stars and dark matter (blue shades) was extracted using visible-light images from HST. Chandra data was used to locate the X-ray emission from intracluster gas (pink shades), constituting the majority of visible matter. Credits: [20] . . . . . . . . . . . . . . . . . . . . . . . Figure 1.4 Visual illustration of the multipole expansion of the cosmic microwave background temperature distribution. Credits: [25]. . . . . . . . . . . . . . . . . . . . . . . Figure 1.5 CMB power spectrum measured by the Planck collaboration [26]. The ΛCDM spectrum best fit is plotted in light blue. Residuals with respect to this model are shown in the lower panel. The error bars show ±1σ uncertainties. The vertical scale changes at l = 30, where the horizontal axis switches from logarithmic to linear. Figure 1.6The mass range spanned by dark matter candidates.

Figure 1 . 7 11 Figure 1 . 8 13 Figure 1 . 9

 1711181319 Figure 1.7 Comoving number density Y (left) and resulting thermal relic density (right) of a 100 GeV/c 2 , P-wave annihilating dark matter particle as a function of temperature T (bottom) and time t (top). The solid contour is for an annihilation cross section that yields the correct relic density, and the shaded regions are for cross sections that differ by 1, 2, and 3 orders of magnitude from this value. The dashed contour is the number density of a particle that remains in thermal equilibrium. Credits: [42] . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Figure 1.8 Feynman diagram illustration of dark matter detection strategies. The arrow sets time direction and identifies the detection strategy. . . . . . . . . . . . . . . . . . . . . 13 Figure 1.9 Signal channels of dark matter-induced scatterings in direct detection searches. Detection technologies based on one or more such channels are reported. Figure adapted

Figure 1 . 10

 110 Figure 1.10 Differential scattering rates for silicon (red), argon (blue), germanium (black), and xenon (green), for WIMP masses:

Figure 1 . 11

 111 The WIMP search landscape. Current best exclusion limits (from a variety of experiments) are given by the gray dashed line. Sensitivity projections are presented as solid lines. TPC experiments are approaching the neutrino floor (fog)[START_REF] Billard | Implication of neutrino backgrounds on the reach of next generation dark matter direct detection experiments[END_REF][START_REF] Ciaran | New Definition of the Neutrino Floor for Direct Dark Matter Searches[END_REF], where a potential dark matter signal will become hidden underneath coherent elastic neutrino-nucleus scattering. Semiconductor detectors and bolometers are set to explore a vast portion of the light WIMP parameter space (0.1 -10 GeV/c 2

Figure 2 . 14 Top: 40 Figure 2 . 15 42 Figure 2

 21440215422 Figure 2.14 Top: Tracks in a fraction of CCD image. Noise can be observed in the rest of the image as pixel value fluctuates about the pedestal (i.e., the value of a pixel empty of charge in ADU). The bottom scale correlates the pixel value in ADU to its color in the image. Bottom: 50 × 50 pixels portion of CCD image. Cluster topologies associated to various particles interacting with the CCD are shown and labeled. The muon track extremities have different widths by virtue of the different interaction depths. Only pixels with energy > 0.1 keV are colored for improved contrast. . . . . . . . . . . . . . . . 40 Figure 2.15 The DAMIC at SNOLAB apparatus. (a) The 4k × 4k CCD in its copper tray. (b) The IR-shield OFHC copper box. The uppermost CCD, Extension 1, is sandwiched between two Roman lead blocks (c) The invacuum components and the copper vacuum vessel. (d) The 20 cm lead castle and the 42 cm polyethylene shielding. . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Figure 2 . 17

 217 Figure 2.17 DAMIC diffusion model. The reconstructed cluster spread is related to the interaction depth using cosmic muon tracks (dashed line). The baseline model uncertainty band (E = 0 keV ee ) and solid lines accounting for linear energy corrections at E = 10, 20 keV ee are shown.Energies are expressed in electron-equivalent units. . .

Figure 2 . 18 Top:

 218 Figure 2.18 Top: Energy spectrum obtained illuminating the CCD from the back with a 55 Fe source. The two main peaks represent the (daughter) Mn nucleus K α and K β lines. The observed Al K X-ray is produced in the source holder. Manganese escape lines appear, due to partial energy deposits, with the subsequent escape of the Si fluorescence X-ray (1.7 keV). Bottom: Calibration constant measured at various energies divided by its value at 5.9 keV ee . Red points are measured using optical photons from a red LED. Black points are measured using X-ray photons from fluorescence of Al, Cr, Fe, Mn, O and Si. The energy response of the CCD is demonstrated to be linear within 5% down to 40 eV ee . . . . .

Figure 2 . 19

 219 Figure 2.19 Ionization energy signal in keV ee as a function of recoiled nucleus energy in keV nr . DAMIC results are reported as a dashed line. The gray band represents the 1σ uncertainty range. Previous low-energy measurements and the expected values from the Lindhard model are also reported. . . . . . . . . . . . . . . . . . .

Figure 2 . 20

 220 Figure 2.20 Mean pedestal-subtracted pixel value in ADU as a function of the row number. Dataset acquired with 1 × 100 binning. Rows up to 42 show a non-zero mean pixel value; past 42, in the vertical overscan, they are consistent with zero. The higher amount of charge seen for CCDs 2 and 7 can be ascribed to light leaks inside the copper box. . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 3 . 1 52 Figure 3 . 2 54 Figure 3 . 3 E 55 Figure 3 . 4 57 Figure 3 . 5 57 Figure 3 . 6 64 Figure 3 . 7 65 Figure 3 . 8

 315232543355345735573664376538 Figure 3.1 Portion of image acquired with two amplifiers of the same serial register. Correlated noise is visible as a diagonal pattern. The different background shade in the two images corresponds to the respective digitizer pedestals (i.e., the 0-charge signal). . . . . . . . . . . . . 52 Figure 3.2 Iron masks for the 7 DAMIC CCDs. Masked pixels are represented in blue, retained pixels are represented in red. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Figure 3.3 E-σ x distribution of the DAMIC 1 × 100 data in the WIMP search range. Cluster spread range is 0-1.4 pixels. Energy range is 0-6 keV ee . Events detected by CCD 1 and CCDs 2-7 are displayed in different colors. . . . . 55 Figure 3.4 Log-likelihood ratio distributions for data (red points) and blank images with simulated Poisson dark current (gray points). The chosen analysis threshold is ∆LL = -22, where expected noise clusters are less than 0.1. . . 57 Figure 3.5 Seed and likelihood clustering efficiencies between 50 eV ee and 10 keV ee . The seed clustering efficiencies (dashed lines) are measured by simulating tritium decays in the bulk of the CCD. Shown curves represent: the ideal case without noise (red), with simulated readout noise (blue), and after quality cuts (green). The likelihood clustering efficiency (black solid line) is measured by simulating events uniformly in energy and position onto noise-only images. The plateau at 90% is due to quality cuts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Figure 3.6 Cross-sectional view of the GEANT4 geometry of the DAMIC at SNOLAB detector. Detector parts are colored according to material and background model grouping. Copper parts are 3D-rendered making use of a color gradient. A blow-up of a CCD module with modified aspect ratio is displayed at the bottom. . . . . . . . 64 Figure 3.7 DAMIC at SNOLAB CCD sensor geometry. CCD dimensions are reported in the text. The various layers are colored according to their material. . . . . . . . . . 65

Figure 3 . 9

 39 Figure 3.9 Results from secondary ion mass spectrometry screenings of a DAMIC CCD. Solid (dashed) lines represent measurements done with a fine (coarse) beam width. Shaded areas represent the layered backside structure as extracted from these measurements. From left to right, alternating SiO 2 /polysilicon layers are shown in red/gray, silicon nitride in yellow, ISDP getter in blue and low donor concentration n-type silicon in green. .

Figure 3 . 10

 310 Figure 3.10 Depth distribution of surface contaminants. The analytical form of the distribution is reported in figure. . .

Figure 3

 3 Figure 3.11 GEANT4 standard (black) and reduced (red) energy spectra for 60 Co simulated in copper module base (bottom) plate. The two histograms are compatible within statistical uncertainties. This is better seen considering their ratio reported in the bottom plot. Ratio fluctuations increase as bin statistics decreases. . . . . . . . . .

Figure 3 . 12

 312 Figure 3.12 Spectrum of primary neutrons and other secondary particles that make it through polyethylene and lead shielding. Plot taken from [117]. . . . . . . . . . . . . . . . . .

Figure 3 . 13

 313 Figure 3.13 Neutron production rates from 238 U spontaneous fission (top) and alpha-induced neutron ejection (bottom) in different detector parts. The VIB contribution dominates in both cases. . . . . . . . . . . . . . . . . . . . . .

Figure 3 . 14

 314 Figure 3.14 Wireframe representation of the GEANT4 geometry used to study neutrons produced in the apparatus. The VIB board is labeled in green. . . . . . . . . . . . . . . . . . .

Figure 3 . 15 Top:

 315 Figure 3.15 Top: Discrimination of alphas (triangles) and betas (circles) by means of f pix . Bottom: Discrimination of plasma (orange triangles) and bloomed (purple triangles) alphas using σ x /σ y . . . . . . . . . . . . . . . . . . . . . . .

Figure 3 . 16 A

 316 Figure 3.16 A spatially-correlated 210 Pb-210 Bi candidate decay pair. The first cluster has energy E = 57 keV. The second cluster has energy E = 376 keV with a time separation of ∆t = 1.4 d. . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 3 . 17 78 Figure 3 . 18 81 Figure 3 . 19 82 Figure 3 . 20 87 Figure 3 . 21 1 . 87 Figure 3

 317783188131982320873211873 Figure 3.17 Charge collection efficiency model extracted with simulations (solid) and silicon transport properties (dashed). Sensitive region (wafer) starts in correspondence with the vertical dotted gray line. Normalized units are used: 10 20 cm -3 (donor concentration), 55 × 10 9 µm 2 /(V•s) (mobility), 0.1 V/µm (electric field), and 1.2 × 10 5 s (lifetime). . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Figure 3.18 Data and background model energy projections for CCDs 2-7 (top) and CCD 1 (bottom). Template material histograms are represented in different colors. The region around 8 keV ee is masked due to the inability to model the copper fluorescence line with GEANT4. . . . . . . . 81 Figure 3.19 Data and background model sigma projections for CCDs 2-7 (top) and CCD 1 (bottom). Template material histograms are represented in different colors. Front and back surface contaminants are visible as peaks at low and high values of σ x , respectively. . . . . . . . . . . . . 82 Figure 3.20 Data points (black) overlaid on best-fit energy projection (red) for energy in [0, 6] keV ee . Background-only energy projection (blue) is also shown. Silicon fluorescence region between 1.6 and 1.8 keV ee is masked in the fit. The distribution of events is consistent with the background-only hypothesis down to 200 eV ee . . . . . . 87 Figure 3.21 Data points overlaid on best-fit background model and excess contours for E ∈ [0, 1] keV ee . Open circles correspond to CCDs 2-7, while filled circles correspond to CCD 1. The red contours represent the bulk exponential excess with ε = 67 eV ee . The feature at 0.87 keV ee is the neon Kα fluorescence lines following electron capture in 22 Na in the CCD bulk. . . . . . . . . . . . . . . . 87 Figure 3.22 DAMIC at SNOLAB 90% C.L. upper limit on spinindependent WIMP-nucleon scattering cross section (solid red line). The background-only forecast ±σ band is shown in light red. Exclusion limits (90% C.L.) from DAMIC previous result [97], other experiments [134-138], and the 90% C.L. contours for the WIMP-signal interpretation of the CDMS silicon result [139] are shown. 88

Figure 4 . 1

 41 Figure 4.1 Illustration of the floating diffusion gate. Charge is sensed as a voltage pulse at the output transistor and then flushed out closing the reset switch, setting the buried channel to the reference voltage, V R . Figure adapted from [80]. . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 4 . 2

 42 Figure 4.2 Working principle of a skipper amplifier. Charge is injected into the summing well (SW) from the serial register (SR). The SW pulse creates a temporary potential ladder allowing charge into the sense node (SN), kept at reference voltage V R . After integration, the output gate (OG) is put into its low state, letting carriers back to SW. It then goes back to its high configuration. A SW pulse reinitiates the non-destructive charge measurement cycle. . . . . . . . . . . . . . . . . . . . . . . .

Figure 4 . 3

 43 Figure 4.3 Skipper amplifier 47/6 50× magnification. Clock and bias lines are labeled in black. Additional skipper voltages dump gate (DG) and drain are visible on the righthand side of the sense node. The sense floating gate is embedded in silicon oxide, between output gate (OG) and dump gate (DG). Taken at the Pritzker Nanofabrication Facility of the University of Chicago. . . . . . .

Figure 4 . 4

 44 Figure 4.4 Skipper image resolution measurements for increasing number of skips. The dashed line corresponds to the expected 1/ N skips trend. Red points are measurements of the resolution for number of skips from 1 to 1000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 4 . 5

 45 Figure 4.5 Pixel charge distribution for 1, 100, and 3000 skips. Single electron peaks start being visible at 100 skips. At 3000 skips the resolution equals 7% e -and individual electrons are fully resolved. . . . . . . . . . . . . . . . .

Figure 4 . 6

 46 Figure 4.6 Illustration of the LSM location. The lab facilities are located midway through the Fréjus tunnel, a few hundreds of meters away from the French-Italian border. .

Figure 4 . 7

 47 Figure 4.7 Illustration of DAMIC-M apparatus. The CCD stack lies in an electroformed copper cryostat shielded in a copper box for IR. The detectors are cooled down using liquid nitrogen (LN2). The first layer of shielding is an inner ancient lead castle (∼5 cm). This is surrounded by few tens of cm's of low-activity lead and ∼50 cm cylindrical polyethylene castle. . . . . . . . . . . . . . . 96

Figure 4 . 8 97 Figure 4 . 9

 489749 Figure 4.8 Preliminary design of the DAMIC-M cryostat. The vertical CCD stack is located at the bottom of the cryostat. Kapton cables running along the entire cryostat geometry are also shown. . . . . . . . . . . . . . . . . . . . . . 97 Figure 4.9 DAMIC-M sensitivity projections for spin-independent WIMP-nucleus scattering (top) for nuclear recoil (dashed) and accompanying Migdal electrons (dotted) signals, and hidden-photon kinetic mixing parameter (bottom). 99

Figure 4 100 Figure 4 . 11 102 Figure 4 103 Figure 4

 410041110241034 Figure 4.10 DAMIC-M sensitivity projections for light mediator (top) hidden sector and heavy mediator (bottom) hidden sector dark matter. Heavy mediator case: the labeled thick solid lines in yellow and orange correspond to the expected cross sections for a scalar and fermion candidate, respectively. Light mediator case: the labeled thick solid line in yellow represents the expected cross sections for a freeze-in produced candidate. . . . . . . . . 100 Figure 4.11 Portion of highly defective CCD image from a DAMIC-M pre-production batch. . . . . . . . . . . . . . . . . . . 102 Figure 4.12 DAMIC-M production CCDs fabrication process flow. Companies/locations and images representative of the manufacturing stage are reported on the right-hand and left-hand sides of the process, respectively. . . . . . 103 Figure 4.13 DAMIC-M pre-production wafer diced in four 6k × 1.5k 105

Figure 4 . 14 106 Figure 4 . 15

 414106415 Figure 4.14 Defects in four CCDs diced from a single pre-production wafer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Figure 4.15 Evolution of defects in a PP1 CCD as a function of the substrate voltage . . . . . . . . . . . . . . . . . . . . . . . 107

Figure 4 . 16

 416 Figure 4.16 Fifteen-ton iron castle used for DAMIC-M wafers transatlantic shipment. . . . . . . . . . . . . . . . . . . . . . . . 109

Figure 4 . 17

 417 Figure 4.17 Prototype of DAMIC-M electroformed copper box grown and machined at Canfranc underground laboratory. . . 110

Figure 4 . 18

 418 Figure 4.18 Initial (top) and final (bottom) DAMIC-M detector design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 4 . 19

 419 Figure 4.19 The latest DAMIC-M CCD stack (top) and module (bottom) design. . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 4 . 20

 420 Figure 4.20 Simplified schematics of DAMIC-M electronics chain. Programmable logic is shown in maroon. Mezzanine boards are shown in green. Cold components are shown in gray, inside the cryostat shown in blue. Adapted from [118]. . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 5 . 1

 51 Figure 5.1 DAMIC-M LPNHE cleanroom. Three test setups were present at the time of the picture, two of which operational (orange and blue) . Some of the control/readout electronics (electronic boards, power supplies, etc.) used in these test-chambers can be seen next to the orange cryostat. A light-blue ESD-safe mat can be seen next to the silver cryostat. . . . . . . . . . . . . . . . . .

Figure 5 . 2

 52 Figure 5.2 Assembled blue cryostat. Plates are attached to the cubic base frame. The door-plate can be sealed by means of screw-handles at its edges. . . . . . . . . . . . . . . .

Figure 5 . 3

 53 Figure 5.3 Top: CCD copper support and RTD (far) and resistor (near) aluminum holders attached to its bottom. Bottom Left: CryoTelGT copper cold head coming through the cryostat port. A germanium RTD monitors the cold head temperature. Bottom Right: Copper support screwed to the cooler cold head. Wires deliver electrical current to 25 Ω and 50 Ω resistors. . . . . . . . . . . . . . . . . .

Figure 5 . 4

 54 Figure 5.4 External elements of the blue-cryostat test system cryogenics: cryostat, vacuum pump, pressure gauges, and cryocooler . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 5 . 5

 55 Figure 5.5 Pressure evolution inside the blue test chamber as measured by the cryostat pressure gauge in hPa (1 hPa=1 mbar). Cryocooler cold head temperature is reported as well, in kelvins. . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 5 . 6

 56 Figure 5.6 UW1612S in its aluminum box screwed to the copper support inside the cryostat. A RTD holder is attached to the box using Kapton tape and vacuum grease. The holder carries a PT-102 temperature sensor. . . . . . . .

Figure 5 . 7 124 Figure 5 . 8

 5712458 Figure 5.7 Top: Leach controller and external power supplies. Skipper video traces are visible in the oscilloscope. Bottom: Second stage and breakout boards. Connectors are labeled according to the signals they convey. . . . . . . . 124 Figure 5.8 Simplified schematics of the blue-cryostat test system air-side electronics. Left to right: An ARC-66 PCIe board is installed in the host computer to operate the CCD controller. On the Leach-end, the timing board (ARC-22) manages clock, video and bias boards (ARC-32, -45, -33, respectively). The boards send (receive) clock and bias (video) signals to (from) the breakout board, where they are conveyed on to the second stage board through a 50-pin connection. The second-stage board shapes clocks and amplifies the CCD video signal. A 50-pin feedthrough on the cryostat enables air-vacuum sides transition. The chain continues inside the chamber with a 50-pin Kapton flex cable connecting to the CCD (see Section 5.1.3). . . . . . . . . . . . . . . . . . . 125

Figure 5 . 9 Figure 5 . 10 127 Figure 5 . 11 127 Figure 5 128 Figure 5 . 13 130 Figure 5 . 14

 595101275111275128513130514 Figure 5.9 Top to bottom: Vertical, horizontal and summing well clocks oscilloscope traces. Amplitudes and widths are reported (rounded) as measured with the oscilloscope. Measured values are consistent with configuration file selections. . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Figure 5.10 Vertical clock of Figure 5.9 after RC-shaping in the secondstage board. . . . . . . . . . . . . . . . . . . . . . . . . . 127 Figure 5.11 Setup used to test video lines. A sinusoidal pulse is injected into the video pins at the CCD-end of the flex. A gain of 32 is observed at the Leach end of the chain. The second stage board connected to the cryostat feedthrough can be seen in the left-hand side figure. . . . . . . . . . 127 Figure 5.12 UW1616S in its aluminum package, sitting on ESD-safe bag and box. CCD flex connector is shorted to prevent stray electrostatic charge to seep in. . . . . . . . . . . . . 128 Figure 5.13 Top: UW1612S installed in the blue-cryostat test chamber. Bottom: blue-cryostat setup during commissioning. External electronics and cryostat are visible on upper and lower shelves, respectively. . . . . . . . . . . . . 130

Figure 5 . 15

 515 Figure 5.15Slow control package schematics. Slaves represent machines containing the (or a copy of) database. Only the primary slave containing the master database pertains to the blue-cryostat test system. Taken from[START_REF] Nikkel | Astro-slow-control user manual[END_REF]. . . .

Figure 5 . 16

 516 Figure 5.16 Blue-cryostat test system private internal network. Elements outside the network are shown as well for completeness. Power refers to LPNHE power grid. UPS is the APC SMC1000 uninterrupted power supply. PDU is the power distribution unit used to control pump switch. The TPS compact vacuum pump is connected to the SC machine using a serial RS-232 port, enabling monitoring of pump parameters (e.g. rotation speed) and pump-end pressure gauge. TPG362 is the Pfeiffer pressure controller managing the PKR251 gauge. . . .

Figure 5 . 17

 517 Figure 5.17 Example of alarm management box in the slow control web interface. An alarm is issued when reject temperature is greater than 50 • C. . . . . . . . . . . . . . . . . .

Figure 5 . 18

 518 Figure 5.18 Skipper readout video trace. Three NDCMs are shown. Trace elements are labeled. One NDCM starts with a reset pulse to set the reference voltage. The pedestal is then measured for an integration period t int . Afterwards, charge moves from summing well to sense node (SWHi pulse) and is integrated for t int . The output gate is finally pulsed low (OGLo pulse) to let charge back into SW. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 5 . 19

 519 Figure 5.19 Example of DS9 analysis capabilities. The pixel area inside the green circle is characterized. Next to it, a muon track crossing the CCD from top to bottom can be seen. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 5 . 20 140 Figure 5 . 21 141 Figure 5 142 Figure 5 . 23 144 Figure 5 . 24 145 Figure 5 . 25 147 Figure 5 . 26 148 Figure 5 . 27

 5201405211415142523144524145525147526148527 Figure 5.20 Top (two plots): Single-skip and 1000-skip PVDs. Fit curves to the 0e -peak are reported along with values of σ 0e -and estimated electronic noise. Note that in this case the Leach was operated in inverse charge-ADU mode. Bottom: measured noise (red points) compared to theoretical trend (dashed line). Data and model are compatible. The 100-skip point represents a fit misestimation of the resolution due to yet unresolved single electron peaks. . . . . . . . . . . . . . . . . . . . . . . . . 140 Figure 5.21 Reconstructed skipper images produced with CCDTesting. Major skip CTI is visible as a charge pattern correlated to the event cluster observed in the first three images. Most charge is lost between first and second skip. Standard deviation image is also affected by CTI, since this alters the single-pixel value distribution. . . . . . . . . . 141 Figure 5.22 First-second pixel value difference distribution. Charge loss is manifest as a prominent lower-tail in the otherwise Gaussian PVDD. Reported values of the CTI coefficient and significance indicate important charge loss. 142 Figure 5.23 Dark current Gauss-Poisson convolution fit of 0e -and 1e -electron peaks. Convolution fit (CF) and anticlustering (AC) estimates are reported in title. They are consistent within uncertainties. . . . . . . . . . . . . . . 144 Figure 5.24 Full image skip fast Fourier transform produced with CCDTesting. The wide peaked structure slightly above 5 kHz was observed in both blue and orange test chambers and is thus likely to come from a shared component or connection within the lab. . . . . . . . . . . . . 145 Figure 5.25 Top to bottom: amplifier gain, single-skip noise and average image noise as functions of the integration time. In bottom plots, the green line represents noise before calibration (in ADU units), the red solid line represents noise post-calibration. The latter is to be considered for optimization purposes. . . . . . . . . . . . . . . . . . . . 147 Figure 5.26 Average image pixel value distributions compared at the threshold between V drain and summing well. Lowering V drain by 1 V brings dark current back to nominal levels. PVD fit fails in the top case due to very high dark current. . . . . . . . . . . . . . . . . . . . . . . . . . 148

Figure 6 . 1

 61 Figure 6.1 DAMIC-M clean room planimetry and location inside Laboratoire Souterrain de Modane. A top-view illustration of detector (left) and gowning (right) rooms is shown. Current instrumentation arrangement is reported (not to scale). The black rectangle represents a clean room pillar. Wall thickness is neglected for simplicity. Reported room sizes refer to internal dimensions. Illustrated instrumentation and tools are described in the text. The SuperNEMO experiment is currently under construction near DAMIC-M clean room. LSM rendering shows previous experiment NEMO apparatus. . . .

Figure 6 . 2

 62 Figure 6.2 Copper cryostat (top part) etching in sulfuric acid solution at LPSC. The chemical reaction between copper oxide and sulfuric acid produces water and soluble copper sulphate, which gives the solution its blue color. . .

Figure 6 . 3

 63 Figure 6.3 Closed LBC support structure. Salient elements are labeled. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 6 . 4

 64 Figure 6.4 Rendering of LBC external shielding on support structure. Fixed parts of shielding and support structure are shown on the right. The mobile support hosting lower shielding, cryostat stand (not shown), pump and cryocooler (not shown) is illustrated on the left. Different parts are colored according to legend. Size of shielding parts reported in mm units. . . . . . . . . . . . . . . . .

Figure 6 . 5

 65 Figure 6.5 Left: LBC cryostat after manufacture. The vessel rests upside down relative to its arrangement in the LBC. The bottom part features one vertical and four lateral cross-oriented openings for ports and feedthroughs. Right: Cryostat mechanical drawing with dimensions in mm (side view). . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure

  Figure 6.6Cold table assembly and cryocooler installation on cryo-

Figure 6 . 7 Figure 6 . 8 160 Figure 6 . 9 Figure 6 . 10 Figure 6 . 11 Figure 6 . 13 Figure 6 . 14 167 Figure 6 . 15 168 Figure 6 . 16 FFT 169 Figure 6 170 Figure 6 . 18 FFT 171 Figure 6 . 19 CCD 173 Figure 6 . 20 174 Figure 6 176 Figure 6 . 22 Figure 6 . 23 Figure 6 . 24

 67681606961061161361416761516861616961706181716191736201746176622623624 Figure 6.7 Cold hand and internal shielding installation. Ancient lead parts are labeled. A: Cold hand and fingers mounted on cold arm. Underlying extension cables (and two-toone boards at flange) are installed before cold hand. B: 20 mm thick lead slabs stacked above cold hand. Short (26 mm) Teflon pillars prevent thermal contact. C: Lead castle construction around cold assembly. D: Complete lead castle. Capped flex cable passthroughs show next to copper fingers. All lead tops and caps are ancient. . 159 Figure 6.8 Installation of upper inner lead disks inside the top part of the LBC cryostat. The lowermost disk has a composite structure, consisting of a central 20 mm thick Roman lead disk and a 27.5 mm thick low-background lead centering ring. . . . . . . . . . . . . . . . . . . . . . 160 Figure 6.9 Left: Pump-end of the vacuum chain. Right: Author closing the LBC cryostat with hydraulic crane. Temperature control feedthrough is visible at the cryostat bottom part. . . . . . . . . . . . . . . . . . . . . . . . . . 161

Figure 6 . 25 2 . 182 Figure 7 . 1 Figure 7 . 2 Figure 7 . 3 190 Figure 7 . 4 191 Figure 7 . 5 191 Figure 7 . 6 194 Figure 7 . 7 195 Figure 7 . 8 198 Figure 7 . 9 199 Figure 7 . 10 200 Figure 7 200 Figure 7 . 12

 62521827172731907419175191761947719578198791997102007200712 Figure 6.25 Comparison of 6415 average images in data runs 1 and 2. U amplifier region is zoomed in. Color scale is in electron units. High-energy clusters, transfer inefficiency and amplifier luminescence are suppressed in data run 2. See text for details. . . . . . . . . . . . . . . . . . . . . 181 Figure 6.26 Cold finger RTD measurement during multi-erase temperature cycle. The 1-hour multi-erase loop runs throughout the entire temperature cycle. Temperature is raised by 10 K at a time, with a ramp rate of 0.1 K. . . . . . . 182 Figure 7.1 Top: Heavy mediator differential rate for 10 MeV (teal) and 100 MeV (red) dark matter. Cross section values are adjusted to obtain the same number of events. Heavier particles produce higher energy signals. Bottom: Ultralight mediator differential rate for 10 MeV (teal) and 100 MeV (red) dark matter. Cross section values are adjusted to obtain the same number of events. Heavier particles produce higher energy signals. . . . . . . . . . 187 Figure 7.2 Charge differential rates for heavy mediator 10 MeV dark matter. Red (teal) histogram represents the rate obtained with pair-creation probabilities provided in [190] (dividing simulated energy deposition value by 3.75 eV mean electron-hole ionization potential). . . . . 188 Figure 7.3 Charge diffusion and 10 × 10 binning PCDs. In prediffusion entries, charge is injected at a given spatial point in the CCD and ascribed to a single pixel. Post diffusion, event charge is redistributed over different pixels according to diffusion dynamics. Post-binning histogram is produced by cumulating charge from 100pixel sized squares across the pixel area. Number of entries for the different histograms is reported in legend.190

Figure 7 . 13

 713 Figure 7.13 Top: DAMIC-M LBC heavy mediator dark matter-electron scattering cross section 90% C.L. exclusion limits. Bottom: DAMIC-M LBC ultra-light mediator dark matterelectron scattering cross section 90% C.L. exclusion limits. Results from other dark matter experiments areshown for comparison[START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF][START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF][START_REF] Aprile | Light Dark Matter Search with Ionization Signals in XENON1T[END_REF][START_REF] Aprile | Emission of single and few electrons in XENON1T and limits on light dark matter[END_REF][START_REF] Cheng | Search for Light Dark Matter-Electron Scattering in the PandaX-II Experiment[END_REF][START_REF] Agnes | Search for dark matter particle interactions with electron final states with DarkSide-50[END_REF][START_REF] Barak | SENSEI: Direct-Detection Results on sub-GeV Dark Matter from a New Skipper CCD[END_REF][START_REF] Arnaud | First Germanium-Based Constraints on Sub-MeV Dark Matter with the EDELWEISS Experiment[END_REF][START_REF] Agnese | Erratum: First Dark Matter Constraints from a Super-CDMS Single-Charge Sensitive Detector[END_REF]. Benchmark models taken from[START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]. . . . . . . . . . . . . . . . . . .

Figure 7 . 14

 714 Figure 7.14 Heavy (top) and ultra-light (bottom) mediator upper limits and sensitivity line with ±1σ and ±2σ uncertainty bands. In both cases, at high masses the limit deviates from the sensitivity by more than +2σ due to few 3-e -and one 4-e -counts. . . . . . . . . . . . . . .

  Evidence in Astrophysics and Cosmology . . . . . . . . . . . . . Galactic rotation curves . . . . . . . . . . . . . . . . . . . 1.1.2 Galaxy Clusters . . . . . . . . . . . . . . . . . . . . . . . . 1.1.3 Cosmic Microwave Background . . . . . . . . . . . . . . 1.2 Candidates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Particle Dark Matter . . . . . . . . . . . . . . . . . . . . . 1.3 Direct Detection of Particle Dark Matter . . . . . . . . . . . . . . Scientific Charge-Coupled Devices . . . . . . . . . . . . . . . . .

	1 dark matter
	1.1 1.1.1 2 the damic experiment at snolab
	2.1

-3 e -/pixel/day) are measured with respect to SNOLAB detectors, highlighting two potential setbacks for DAMIC-M. Despite this, the first science dataset acquired with both LBC skipper CCDs (∼20 g) is used to set world-class exclusion limits on the dark matter-electron scattering cross section. xiv C O N T E N T S 2.1.1 Working Principles . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Sources of Noise . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 CCD Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The DAMIC Detector . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Detector Calibrations . . . . . . . . . . . . . . . . . . . . . 3 the damic at snolab background model 3.1 Data Acquisition and Processing . . . . . . . . . . . . . . . . . . 3.1.1 Seed Clustering . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Likelihood Clustering . . . . . . . . . . . . . . . . . . . . 3.2 Detector Modeling and Background Rejection . . . . . . . . . . 3.2.1 Sources of Background in DAMIC at SNOLAB . . . . . 3.2.2 Background Model Constraints . . . . . . . . . . . . . . . 3.2.3 GEANT4 Simulations . . . . . . . . . . . . . . . . . . . . 3.2.4 Measurement of CCD Bulk Contaminants . . . . . . . . 3.2.5 Partial Charge Collection . . . . . . . . . . . . . . . . . . 3.3 Background Model and WIMP Search . . . . . . . . . . . . . . .

3.3.1 Background Model Construction . . . . . . . . . . . . . .

  The Standard Halo Model and PhystatDM recommendations differ for the velocity distribution parameters. Table 1.1 reports the Standard Halo Model (SHM) and PhystatDM (PDM) recommended values, respectively.

Table 1 .

 1

		3 )	(km/s)	(km/s)	(km/s)
	SHM	0.3	220.0	544.0	232.0
	PDM	0.3	238.0	544.0	250.2

1: Dark matter galactic halo model parameters Standard Halo Model (top line) and PhystatDM (bottom line) recommendations. Local dark matter density ρ χ and Speeds v 0 (galactic DM speed), v esc (galactic escape speed) and v E (mean Earth velocity relative to galactic center) are reported.

1.04 1.06 1.08 X-rays Optical photons Figure 2.18: Top: Energy spectrum obtained illuminating the CCD from the back with a 55 Fe source. The two main peaks represent

	the (daughter) Mn nucleus
	K α and K β lines. The observed Al K X-ray is produced in the source
	holder. Manganese escape lines appear, due to partial energy deposits,
	with the subsequent escape of the Si fluorescence X-ray (1.7 keV). Bot-
	tom: Calibration constant measured at various energies divided by its
	value at 5.9 keV ee . Red points are measured using optical photons from
	a red LED. Black points are measured using X-ray photons from fluores-
	cence of Al, Cr, Fe, Mn, O and Si. The energy response of the CCD is
	demonstrated to be linear within 5% down to 40 eV ee .

  .1 in keV/ADU and ADU/e -units. The latter quantity is often referred to as gain.

	CCD Extension	1	2	3	4	6	11	12
	k E (0.26 eV/ADU)	1.01	0.96	0.98	0.98	1.01	0.97	1.00
	k e (ADU/e -)	14.3	15.15	14.8	14.7	14.4	14.9	14.5

Table 2 . 1 :

 21 DAMIC operating CCDs calibration constants in keV/ADU and ADU/e -

	units. The two units are related by the mean electron hole ionization po-
	tential, which is assumed equal to 3.8 eV. This value is used in all DAMIC
	results that follow, unless otherwise specified.

Table 2 .

 2

	CCD Extension	1	2	3	4	6	11	12
	CCD Number	1	2	3	4	5	6	7
	DC (10 -3 e -/pix/day) 0.95	2.64	0.63	0.58	0.71	1.64	5-9

2 reports the dark current measured for the 7 CCDs. Values reflect what is seen in Figure 2.20.

Table 2 .

 2

2: DAMIC CCDs dark current. The correspondence between CCD extensions and numbers is reported. Values for CCDs 2, 6 and 7 reflect the higher amount of charge visible in Figure

2

.20. In DAMIC work

[START_REF] Aguilar-Arevalo | Constraints on Light Dark Matter Particles Interacting with Electrons from DAMIC at SNOLAB[END_REF]

, CCD 4 was demonstrated to have the lowest dark current ever measured.

Table 3 .

 3

1: Activities used to constrain DAMIC background model in µBq/kg. Values measured by means of mass spectrometry are denoted with an [M] subscript. Subscript [G] labels results of germanium gamma spectrometry. The relative publications are cited where available. NM and NA stand for "not measured" and "not applicable", respectively.

  2.1: primordial chains and cosmic activation. Separate simulations were carried out to demonstrate neutron backgrounds are negligible. Based on previous arguments, no simulations were conducted to assess the cosmic muons contribution. Some cosmogenic isotopes such as87 Rb and 137 Cs were eventually excluded due to their subdominant contribution. The relevant low-energy backgrounds are modeled simu-

lating up to 5 × 10 8 beta/gamma decays in 64 unique volumes. The number of decays is chosen to ensure sufficient statistics for each isotope. Table

3

.2 lists the isotopes simulated for the construction of the DAMIC background model. Radioactive nuclei are simulated uniformly throughout detector volumes and across few tens of micrometers into their surface (where applicable).

  -32 spatial coincidence Two32 Si-32 P searches are conducted to minimize event overlaps with 210 Pb-210 Bi. Search (1a) is performed above the 210 Pb Q value, thus no overlap is possible. Search (1b) uses a separation time lower bound of 25 days, corresponding to 5 • t 1/2 for 210 Bi , but only 1.75 • t 1/2 for 32 P. Table3.3 reports the results of the search. The final measurement for the32 Si activity is given by the weighed average of activities

	from (1a) and (1b), equal to 140 ± 30 µBq/kg.
	lead-210 spatial coincidence	The CCD thickness profile of lead-210
	contamination is unknown. However, selection efficiency is highly dependent
	on contamination whereabouts. Given this uncertainty, a constraint is set on
	the bulk lead-210 content, making the highly conservative assumption that
	all identified coincident pairs are thereby located. Table 3.3 reports the results
	Isotope	ε sel	ε t	N pairs	N acc	N overlap	Activity
								(µBq/kg)
	32 Si (1a)	0.398	0.701		26	6.5(1)	0	120(30)
	32 Si (1b)	0.521	0.169		17	3.0(1)	1.3(3)	260(80)
	210 Pb	0.981	0.748		69	2.5(1)	1.9(5)	< 160
			Number of accidentals and selection efficiencies are computed
		using GEANT4 simulations. The former is extracted by performing the search
		on simulated data with spatially randomized clusters. Such operation is reit-

erated 1000 times and N acc is extracted as the sample average. Selection efficiencies are calculated by carrying out the search on simulated data, dividing the number of identified decay pairs by the number of simulated ones. siliconof the lead-210 search. The obtained upper limit of 160 µBq/kg is orders of magnitude better than customary assay techniques to measure bulk lead-210 in materials

[START_REF] Bunker | Evaluation and mitigation of trace 210Pb contamination on copper surfaces[END_REF][START_REF] Abe | Identification of 210 Pb and 210 Po in the bulk of copper samples with a low-background alpha particle counter[END_REF]

.

Table 3 .

 3

3: Results of silicon-32 (1a) and (1b) and lead-210 searches. Uncertainties on the reported quantities are given in parentheses.

  two-dimensional binned-likelihood fit to data in the E-σ x space. A single likelihood analysis is carried out, for CCDs 2-7. Given its different background environment, CCD 1 data is reserved for validation. The construction is carried out between 6 and 20 keV ee (fit region). The lower bound is chosen taking into account WIMP sensitivity and limits set by other experiments. No low-mass WIMP signal is expected above 6 keV ee in DAMIC CCDs. The upper bound is chosen in order to include the full tritium spectrum.11 Model is then extrapolated below 6 keV ee (region of interest) separately for CCD 1 and CCDs 2-7. Background model and data are then used to conduct a likelihood ratio hypothesis test to search for WIMPs.

final background simulations were conducted at the IN2P3 Computing Centre cluster in Lyon, processing (detector response, clustering, etc.) was performed at the University of Chicago. The background model is constructed by performing a 3.3.1 Background Model Construction Over 1000 isotope-volume combinations are simulated. Their output is sorted in 49 templates by detector part and decay chain. Materials are grouped as in Table 3.1, with additional subdivision of the copper into vessel, box, and modules due to different activation. Isotopes are sorted according to Table 3.2.

  .4 reports the best-fit activities for the 49 volume-isotope templates. The corresponding background rates are: • 8.29 dru for E ∈ (6, 20] keV ee (CCDs 2-7) • 3.70 dru for E ∈ (6, 20] keV ee (CCD 1).

	Background Model	CCD Surface
	CCD	Module Screws
	Kapton Cable	Copper Box
	Copper Modules	Copper Vessel
	Ancient Lead	Data
	Similar considerations hold for the WIMP search region of interest (post back-
	ground model extrapolation), with the background budget dominated by in-
	CCD contaminants. The total measured background rates are:
	• 12.28 dru for E ∈ [1, 6] keV ee (CCDs 2-7)
	• 6.22 dru for E ∈ [1, 6] keV ee (CCD 1)

  Data and background model sigma projections for CCDs 2-7 (top) and CCD 1 (bottom). Template material histograms are represented in different colors. Front and back surface contaminants are visible as peaks at low and high values of σ x , respectively.

	Background Model CCD Kapton Cable Copper Modules Ancient Lead Chain 238 U 226 Ra 232 Th 40 K 22 Na 32 Si 3 H 210 Pb 210 Pb 210 Pb 238 U 226 Ra 210 Pb 232 Th 40 K 60 Co 238 U 226 Ra 210 Pb 40 K 60 Co 238 U 226 Ra 232 Th 40 K 60 Co 238 U 226 Ra Detector Part CCD (front srf.) CCD CCD CCD CCD CCD CCD CCD CCD (back srf.) CCD (wafer srf.) Copper Box Copper Box Copper Box Copper Box Copper Box Copper Box Copper Mod. Copper Mod. Copper Mod. Copper Mod. Copper Mod. Kapton Cable Kapton Cable Kapton Cable Kapton Cable Kapton Cable Ancient Lead Ancient Lead Chain Ancient Lead 210 Pb Ancient Lead 232 Th Ancient Lead 40 K Outer Lead 238 U Outer Lead 226 Ra Outer Lead 210 Pb Outer Lead 232 Th Outer Lead 40 K Module Screws 238 U Module Screws 226 Ra Module Screws 210 Pb Module Screws 232 Th Module Screws 40 K Module Screws 60 Co Copper Vessel 238 U Copper Vessel 226 Ra Copper Vessel 210 Pb Copper Vessel 232 Th Copper Vessel 40 K Figure 3.19: Detector Part Copper Mod. 232 Th Copper Vessel 60 Co	CCD Surface Module Screws Copper Box Copper Vessel Data Best-fit Activity 9.86 µBq/kg 4.79 µBq/kg 6.56 µBq/kg 0.42 µBq/kg 340(60) µBq/kg 150(30) µBq/kg 330(90) µBq/kg 69(12) nBq/cm 2 < 0.1 nBq/cm 2 56(8) nBq/cm 2 110 µBq/kg 120 µBq/kg 10(6) mBq/kg 36 µBq/kg 28 µBq/kg 280(30) µBq/kg 110 µBq/kg 120 µBq/kg 15(4) mBq/kg 28 µBq/kg 130(10) µBq/kg 59(5) mBq/kg 7(5) mBq/kg 32.0(5) mBq/kg 29(2) mBq/kg 140(10) µBq/kg 21 µBq/kg 230 µBq/kg Best-fit Activity ∼33 mBq/kg ∼2.3 µBq/kg 5.3 µBq/kg 12 µBq/kg 190 µBq/kg 18(5) Bq/kg 4.2 µBq/kg 200 µBq/kg 20(40) mBq/kg 1.4 mBq/kg 27(8) mBq/kg 24(16) × 10 -1 mBq/kg 28(15) mBq/kg 89(9) µBq/kg 110 µBq/kg 120 µBq/kg 20(8) mBq/kg 36 µBq/kg 28 µBq/kg 36 µBq/kg 400(440) µBq/kg
		(Table continued)

Table 3 .

 3 Discussions on the subject are resumed inChapter 4, where measures designed to meet the ambitious DAMIC-M background goals are detailed.3.3.2 A 11 kg-day WIMP searchThe background model is exploited to search for light WIMPs (1 GeV < mc 2 < 10 GeV) between 50 eV ee and 6 keV ee . The search is carried out on the same 11.6 kg-day exposure dataset used to build the background model. Some images with higher dark current (due to temperature cycling) are excluded, for a final total exposure of 10.93 kg-day.13 Only events reconstructed by likelihood clustering are considered since this is optimized for low-energy point-like interactions. The profile likelihood ratio method[START_REF] Cowan | Asymptotic formulae for likelihood-based tests of new physics[END_REF] is used to test the background-only hypothesis against the low energy signal hypothe-

	modules and vessel (3.61 dru in total), evenly contributed by primordial and
	cosmogenic components, and to a lesser degree (∼15%) from a mixture of
	other materials (lead, kapton cables and module screws). In the case of CCD
	1, the one salient difference consists in the negligible fraction of events from
	copper modules, consistent with observations between 6 and 20 keV ee . For a
	detailed account of rates of specific isotope-material combinations, the reader

4: Best-fit activities of the 49 templates used for the construction of DAMIC at SNOLAB radioactive background model. For CCDs 2-7, bulk tritium (2.86 dru), front-surface 210 Pb (1.45 dru) and wafer-surface 210 Pb (2.43 dru) contribute more than half the observed rate (∼55%). The remaining ∼45% comes largely from copper parts (∼30%): box, can consult reference [58]. These results are crucial to inform mitigation strate-gies in future CCD experiments. sis. The expected WIMP signal rate for a given mass is assumed exponentially decaying as a function of energy. Such dependence is enforced onto an otherwise uniform energy-depth signal probability density function corrected with the detector response:

  CCDSequencer provides the timing waveforms defining exposure, transfer and readout phases. A sequencer file is written for this purpose. The CCDDrone package defines and executes the procedures routinely performed during data acquisition. CCDDrone was expanded at LPNHE for specific needs that arose during R&D. A generic acquisition session makes substantial use of CCDDrone. Its executables will be discussed in next Section 5.1.3. To test Leach clocks and bias signals it was sufficient to start up the controller and apply settings (clock amplitudes and widths, bias values and integration periods).

	• Leach communication
	• Leach clock/bias testing
	• Full-chain clock/bias testing
	• Full-chain video testing.
	Breakout and second-stage boards were tested at UW before shipment to
	LPNHE. Similarly, cables were all tested individually after manufacture at
	the LPNHE electronics workshop.
	The first set of tests enabled the commissioning of the Leach controller for
	operation. Power supply and housing were connected via a shielded power
	cable and PCBs were hooked onto the backplane in the housing. The PCIe
	board was mounted in the host machine 2 . Housing and machine were then
	connected using fiber optic cables. The status of two LEDs on the timing
	board signals when communication is correctly established. Control firmware

was developed at UW

[START_REF] Mitra | [END_REF][START_REF] Mitra | [END_REF]

. They were installed in the host machine. In particular,

  steps. The thermal chain is composed of a cold mass table that is put into thermal contact with the cryocooler cold head via a copper strap.The table stands on the bottom flange of the cryostat, supported by Teflon (PTFE) pillars limiting heat conduction across the two parts. Two Lakeshore PT-103 platinum RTDs and 25 Ω and 50 Ω cartridge heaters are epoxied inside dedicated mount holes at the table base. Temperature control is done with a Lakeshore 336, with control loop set on one sensor and one resistor.

Figure 6.6: Cold table assembly and cryocooler installation on cryostat bottom part. A: Cold mass table mounted on copper flange. Teflon support pillars thermally insulate table from flange. Two RTDs and two heaters are epoxied inside dedicated holes at the table base. B: Cold copper arm and strap mounted on mass table. The strap is put into thermal contact with the cryocooler, but electrically insulated. C: Cold table assembly installed in cryostat bottom flange. D: Cryocooler mounted on lateral flange. The polyethylene piece was machined to accommodate the cryocooler. installation

  .1.

	CCD-Amp.	σ ro	σ avg	σ avg • N skips	Gain
		(e -)	(e -)	(e -)	(ADU/e -)
	6414-L2	∼15	0.232(8)	5.9(2)	9.5(2)
	6414-U2	∼15	0.24(1)	6.1(2)	9.1(3)
	6415-L2	∼15	0.235(9)	6.0(2)	9.0(3)
	6415-U2	∼15	0.213(6)	5.4(1)	9.6(2)

Table 6 . 1 :

 61 Measured noise for 6414 and 6415 L and U amplifiers. Single-skip noise is denoted as σ ro ; σ avg is the average image resolution for 650 skips. Extrapolated single-skip noise and gain are also reported. Much of the correlated noise affecting CCDs is averaged out.

  Equation 6.1 breaks down the number of expected >2e -pixels into two components: dark current and spurious counts from neighboring peaks. The dark current contribution can be approximated to the number of 3e -events for rates measured with 6415. The spurious contribution is dominated by peaks with lower numbers of electrons for dark currents of interest, given Poisson law. The two terms are given by Equation6.2 and Equation 6.3, respectively.Quantities P G and P denote normal cumulative distribution function and Poisson distribution, respectively. Lower threshold to consider a count >2e -

Table 6

 6

	.2. Note that clock-

Table 6 . 2 :

 62 Measured dark rates for CCDs 6414 and 6415 L and U amplifiers. Dark current and clock-induced charge contributions are expressed in (e -/pixel/d) and (e -/pixel), respectively. Statistical uncertainties are reported with the former. Order of magnitude bounds are provided for the latter.

Table 7 . 1 :

 71 Dark matter galactic halo model parameters used in DAMIC-M hidden sector analysis. Speeds v 0 (galactic DM speed), v esc (galactic escape speed) and v E (mean Earth velocity relative to galactic center) are used to compute the inverse mean speed.

  1 is the number of interest. This identity is expressed in Equation 7.8.In practice, the procedures to find sensitivity and upper limits have important differences. In the former case, the test statistic median computed on background-only datasets, med{f(t σ |H 0 )}, is extracted starting from relatively small σ e values. Monte Carlo background-only datasets are produced for the purpose. The cross section is increased until t σ = med{f(t σ |H 0 )} verifies Equation7.8, with f(t σ ) = f(t σ |H 1 ) computed on simulated datasets with σ e > 0. The corresponding σe represents the experiment median sensitivity for the mass point under study. Uncertainty bands around the sensitivity can be computed in a similar manner by settingt σ = med{f(t σ |H 0 )} + Q i ,where Q i are the first and last 15.87% (for ±1σ) and 2.5% (for ±2σ) quantiles of f(t σ |H 0 ), respectively, with i = {first, last}. Asymptotic expressions can be used for f(t σ |H 0 ) and f(t σ |H 1 ) if Wilks theorem hypotheses are fulfilled

		+∞
	σe :	t σ dt σ f(t σ ) = 0.1	(7.8)

  Seed clustering is used for laterally and diagonally adjacent pixels with threshold p th > 3σ avg (all pixels) and seed p seed > 10σ avg ≈ 2e -(at least one pixel). Only candidate clusters with total charge q > 100 e -are masked. Others are attributed to noise. A total of 1599 and 1406 clusters are found for CCDs 6414 and 6415, respectively.

	6. Cluster Mask
	High-multiplicity clusters and any residual CTI are masked by rejecting
	2-10 × 2-10 binned pixel boxes, where the 2 preceding and 10 succeeding bins relative to all cluster pixels are masked.
	7. Correlated Noise Rejection
	Same-image mirror pixels such that |p i -med{p i }| > 100 ADU (i: skip
	number) for any same skip are rejected.
	8. Hot Column Mask
	Hot columns are masked in all images. Hot column identification pro-
	ceeds as follows. The total column charge is profiled (clusters are ex-
	CCD-Amplifier	N. Hot Columns	Unmasked area
			(including cls. mask)
	6414-L2	67	77.01%
	6414-U2	24	89.37%
	6415-L2	35	86.92%
	6415-U2	34	87.95%

cluded) using all images from the science run. A second order polynomial is fitted and then subtracted to the profile to account for any column dependence in dark current. The column charge distribution is thus characterized. Columns out of the [-2.5σ, 2.5σ] range are rejected. The column charge profile for amplifier L of CCD 6414 is shown in Figure 7.8. Table 7.2 reports number of masked columns and corresponding unmasked area for LBC CCDs. A net charge difference between the two halves of the column range is visible, possibly due to residual amplifier light. This is modeled at the inference level to account for different dark currents in the corresponding regions (see Section 7.3).

Table 7 . 2 :

 72 Hot columns masked in Science Run 3. Residual CCD exposed area is reported in percentage units.

  Steady State Continuous Readout 0.01 e /bin -56+56 g d 5x5 Steady State Continuous Readout 0.01 e /bin -56+56 g d 10x10 Steady State Continuous Readout 0.01 e /bin -56+56 g d 10x10 Steady State Continuous Readout 0.01 e /bin -112+112 g d 5x5 Quarter Image Post-Clean -0.003 e /bin 56+56 g d 10x10 Quarter Image Post-Clean 0.003 e /bin -56+56 g d 10x10 4CR + 1QIPC 0.01+0.003 e /bin -112+28 g d

			LBC Continuous Readout Vs Post-Clean Image Sensitivity Forecast
		10 34
		10 35
	]
	e [cm 2	10 36
		10 37
		10 1	mass [MeV]	10 2	10 3

10x1

  ).Credits:[START_REF] Billard | Direct Detection of Dark Matter -APPEC Committee Report[END_REF]. . . . . . . . . . . . . . . . . . . . . . . . . . 18 Figure 2.1 A DAMIC 4k × 4k CCD in its copper module, ready to be installed in the DAMIC apparatus. The Kapton cable transports clock, bias and video signals to/from the CCD. . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Transfer across two pixels in the ŷ direction. The clocking sequence is shown on the right-hand side. State 1 shows the pixel accumulation phase. State 2 shows clock 1 set to low with charge redistributing accordingly. In state 3, clock 2 is set high and charge gathers in the clock 1 region. Similar sequencing is employed to get to state 7, that completes transfer across the two neighboring pixels. Left-hand side top and bottom images show charge (pixel structure not to scale) during states 1 and 7, respectively. . . . . . . . . . . . . . . . . . kHz, flicker noise is up to a factor of 10 larger than flatspectrum white noise. Above 1 kHz white noise takes over; flicker noise sets the CCD noise floor. . . . . . . . 35

	Figure 2.10	Figure 2.6 White (red) and flicker (teal) noise spectra. Below 1
	Figure 2.2 Figure 2.11	Band structure for pure silicon and silicon with donor Portion of CCD image affected by amplifier glowing.
		impurities. The energy gap between valence and con-IR light events are visible as a background gradient
		duction bands spans about 1.16 eV. The presence of a in both the vertical and horizontal directions. Several
		phosphorous atom introduces a discrete energy level particle tracks also appear as black clusters of pixels
		0.05 eV from the conduction band. . . . . . . . . . . . . 24 with various different shapes. . . . . . . . . . . . . . . . 36
	Figure 2.3 Figure 2.12	Representation of an np junction. Electron (blue) and CCD image track zoom-in. The image is affected by sig-
		hole (red) concentrations dominate on opposite sides. Figure 2.7 Salient elements of charge transfer. A fraction of a CCD nificant serial charge transfer inefficiency. Charge be-
		They gradually fall off across the junction and become grid is shown with a readout amplifier in the bottom longing to the particle track is smeared in the hori-
		subdominant. The net effect is the formation at the right corner. In order to get to the readout stage, charge zontal direction. Image equalization is chosen to em-
		junction of an electrically charged region depleted of is transferred across different rows by means of paral-phasize track and associated CTI against noise in the
		mobile charges (delimited by dashed lines). Red and lel clocks. No transfer occurs across the horizontal di-
		blue shaded areas have positive and negative net charge rection in ordinary rows thanks to implanted channel
			stops. The last vertical transfer occurs across the trans-
	Figure 2.5	Cross-sectional view of a DAMIC CCD pixel showing
		the trend of the electric potential across the different
		layers constituting the MOS sandwich. The potential
		well associated to the buried channel is located in the
		1-µm thick p-doped layer. Holes produced following
		an energy deposition in the pixel will drift towards the
		buried channel, where they are stored prior to transfer.
		Electrons drift towards the backside contact where the Figure 2.9 Top: Conventional CCD video output trace (drawing).
		substrate voltage is applied, and are not measured. . . 28 The summing well pulse pinpoints pixel charge injec-
			tion from the summing well into the sense node. Typ-
			ical values for the integration time are between 10 µs
			and 100 µs. Reset and summing well pulse amplitudes
			are typically between 1 V and 10 V. Bottom: Compar-
		Figure 1.12	Dark matter-electron scattering sensitivities for heavy ison of CDS performed with strong high-and low-
			mediator dark matter in silicon (solid) and germanium frequency noise components. CDS integration signif-
			(dashed) targets of 1 (blue), 5 (green) and 10 (red) elec-icantly suppresses high-frequency noise components,
			trons. Solid black line shows exclusion limits from XENON10 but is not effective against low-frequency noise. . . . .

[START_REF] Essig | First Direct Detection Limits on Sub-GeV Dark Matter from XENON10[END_REF]

for reference. Credits:

[START_REF] Essig | Direct detection of sub-GeV dark matter with semiconductor targets[END_REF]

. . . . . . . . . . . . . . . 19 densities, respectively. . . . . . . . . . . . . . . . . . . . 26 Figure 2.4 Pixel cross sectional view. The pixel is akin to a MOS capacitor consisting of polysilicon metal gate electrodes interfaced to a pn-junction by means of a silicon insulator compound. . . . . . . . . . . . . . . . . . . . . . . . 27 fer gate: a potential barrier meant to control charge flow to the serial register. Charge in the outermost row -the serial register -is transferred towards the readout amplifier by means of fast serial clocks. . . . . . . . . .

Figure 2.8 Top: CCD readout stage micrograph. Image courtesy of PNNL (Pacific Northwest National Laboratory). Key components are labeled. Bottom: Circuit diagram of CCD readout. SW controls charge flow across the output gate. Reset switch clears charge in the buried channel. Output transistor amplifies the measured voltage. CCD layer structure not to scale. . . . . . . . . . . . . . background . . . . . . . . . . . . . . . . . . . . . . . . . 37 Figure 2.13 Calibrated pixel charge distribution of a low-background CCD image. Data follows a Gaussian law in ±3σ range.

Readout noise is ∼1.9 electrons. Few entries with charge 9 e -from energetic events are visible. . . . . . . . . . 39

  6.6 Cold table assembly and cryocooler installation on cryostat bottom part. A: Cold mass table mounted on copper flange. Teflon support pillars thermally insulate table from flange. Two RTDs and two heaters are epoxied inside dedicated holes at the table base. B: Cold copper arm and strap mounted on mass table. The strap is put into thermal contact with the cryocooler, but electrically insulated. C: Cold table assembly installed in cryostat bottom flange. D: Cryocooler mounted on lateral flange. The polyethylene piece was machined to accommodate the cryocooler. . . . . . . . . . . . . . . . 158

Table 1 . 1

 11 Dark matter galactic halo model parameters Standard Halo Model (top line) and PhystatDM (bottom line) recommendations. Local dark matter density ρ χ and Speeds v 0 (galactic DM speed), v esc (galactic escape speed) and v E (mean Earth velocity relative to galactic center) are reported. . . . . . . . . . . . . . . . . . . .

Table 2 .

 2 1 DAMIC operating CCDs calibration constants in keV/ADU and ADU/e -units. The two units are related by the mean electron hole ionization potential, which is assumed equal to 3.8 eV. This value is used in all DAMIC results that follow, unless otherwise specified. . . . . .

Table 2 .

 2 2 DAMIC CCDs dark current. The correspondence between CCD extensions and numbers is reported. Values for CCDs 2, 6 and 7 reflect the higher amount of charge visible in Figure 2.20. In DAMIC work [76], CCD 4 was demonstrated to have the lowest dark current ever measured. . . . . . . . . . . . . . . . . . . . . .

Table 3 . 1

 31 Activities used to constrain DAMIC background model in µBq/kg. Values measured by means of mass spectrometry are denoted with an [M] subscript. Subscript [G] labels results of germanium gamma spectrometry.The relative publications are cited where available. NM and NA stand for "not measured" and "not applicable", respectively. . . . . . . . . . . . . . . . . . . . . . . . . .

Table 3 . 2

 32 Isotopes simulated for the DAMIC at SNOLAB background model construction. Parent chain/origin, isotope, half-life and decay Q value are given. . . . . . . .

Table 3 . 3

 33 Results of silicon-32 (1a) and (1b) and lead-210 searches. Uncertainties on the reported quantities are given in parentheses. . . . . . . . . . . . . . . . . . . . . . . . . .

Table 3 . 4

 34 Best-fit activities of the 49 templates used for the construction of DAMIC at SNOLAB radioactive background model. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

As opposed to, e.g., elliptical galaxies, where the centric motion of stars is more chaotic.

A pure (or intrinsic) semiconductor is free of any impurity (i.e., atoms of a different chemical element) in its lattice.

The widths of parallel and serial clocks are in the order of 10 µs and 0.1 µs, respectively.

For reference, DAMIC CCDs readout noise after parameter optimization is only few electrons.

Hot pixels, columns or rows are regions where intrinsic dark current is high due to lattice defects. These can be caused by mechanical stress or be radiation-induced.

Electron and energy units are related through the mean electron-hole ionization potential in silicon: ε eh = 3.8 eV/carrier.

This is true for the energy range explored by DAMIC CCDs, down to ∼50 eV ee . For energies 1 MeV, the totality of the deposited energy is used for ionization. As energies get smaller, an increasing fraction is lost through phonon exchange. This effect is known as quenching.

The NRIE is also referred to as quenching factor.

This is because charge from multiple pixels is read out at once, and readout noise is taken in for a single measurement. Conversely, in a 1 × 1 dataset, clustering sums up charge and

Saturation happens when the activation rate is less or equal than the decay rate.

The VIB board was only simulated to demonstrate neutrons thereby produced are a negligible source of background. Any other radiation it produces is shielded by the cylindrical lead block underneath.

This information is stored whenever particles interact in the sensitive detector, i.e., the CCD bulk.

This number represents an upper limit because in-vessel detector parts surrounding the CCDs were not simulated to estimate it.

While tritium from the getter layer was excluded from the background model, a significant contribution is expected from silicon activation in the bulk of CCDs[START_REF] Aguilar-Arevalo | Characterization of the background spectrum in DAMIC at SNOLAB[END_REF]

.[START_REF] Rubin | Rotational properties of 21 SC galaxies with a large range of luminosities and radii, from NGC 4605 (R=4kpc) to UGC 2885 (R=122kpc)[END_REF] The simulation efficiency takes into account cluster reconstruction, but also a correction for the fraction of the CCDs that are masked (6.5%), since masks are not simulated.

In practice, the readout time-dark current trade off determines the number of skips that is optimal to perform.

The 47/6 label refers to the width/length (in µm) of the sense node channel of the sourcefollower output transistor.

Copper is used due to its high thermal conductivity, ∼400 W/(m•K).

A Dell OptiPlex 7060 running CentOS 8.

Also, it is generally better to avoid mechanical stress to CCD packages.

If there is no outliers (i.e., charged pixels), median and mean coincide. In general, the median provides a better estimate since it is insensitive to outliers.

Note that no mention is made of other sources of dark counts. These are assumed subdominant here, but will bias measurements if that is not the case.

From now on 1603 for brevity.

The noise trend extracted for average images is more accurate than the single skip case, since it stems from many measurements. Additionally, first skip noise can be higher than

Hereafter, 6414 and 6415.

This value assumes electroformed copper lids. These were recently machined at LSC and will be installed at the LBC in fall 2022.

Here, high-energy refers to ionization events depositing energies 100 eV.

After restart, levels 1 e -/pixel/d could be measured.

A physical signal model for dark photons is currently in the works.

A more accurate modeling approach for this effect is under study for science run 4.

Thanks to the great teachers I found, I could build up solid bases for the years to come. Afterwards, I took up an Erasmus Mundus Joint Master Degree in Experimental Nuclear Physics

Dark count contributions are linked to temperature, clocks and V DD , although more recently glowing was observed for the summing well too. These contributions were considered, too. Shallow depth sites disfavor precision dark current measurements, thus in some cases only qualitative considerations were made. Clock-induced charge was detected in the CCD overscan, but was not estimated due to its low rate combined with low pixel statistics.

Substrate voltage and V DD scans were performed to measure dark current.

Substrate voltage was varied between 20 V and 120 V in steps of 9 V. Dark current only clearly increased from 29 V to 38 V, while for 20 V the CCD was not fully depleted and tracks looked smeared and diffuse, which compromised the measurements. Dependence on V DD was expected for fixed values of the reference voltage. Measurements with Gauss-Poisson convolution fits showed dark count rises below -22 V (amplifier glowing) and above -17 V, with a plateau in between. A precise measurement of steady state dark current was carried out using the CR DAQ strategy at both LPNHE and University of Chicago. Figure 5.27 shows results of both measurements. Normalized by ex- Prominent tail from empty pixel peak is visible on the left-hand side of 1-electron peak.

List of Tables