Bruno Sicardy

Alin Nedelcu

René Duffard

Philippe Rousselot

Pascal Descamps

François Colas

Jérémie Vaubaillon

Florent Deleflie

William Thuillot

Lucie Maquet

Jonathan Normand

Sylvie Lemaître

Rachida Amhidez

Siegfred Eggl

Maria Kudryashova

Daniel Hestroffer

Amélie Muslewski

Sem Bendjeddou

Djamila Houibi

Yohann Gominet

Agnès Patu

Mickaël Gastineau

Et D'

Auriane Egal

Melaine Saillenfest

Eléonore Saquet

William Polycarpe

Bogdan Dumitru

Fatoumata Kebe

A Michael Marsset

Pierre Vernazza

Regina Rudawska

Sylvain Bouley

Rafael Sfair

Juan Quintanilla

Elisa Rojas

María Candelaria

Monica Rodriguez

Brisa Mansillas

Yola Gloaguen

Isabelle Berman

Hervé Gloaguen

Regina De Oliveira

Alberto Gago

Patrizia Pereyra

Francisco De Zela

Jorge Moreno

Jorge Urquiaga

Casio Oré

Carlos Argüelles

Nobar Et D'ailleurs:

Mario Baella

Julio C Zegarra

José Tello

Gonzalo Tancredi

Tabaré Gallardo

Ricardo Gil-Hutton

Marcela Cañada Assandri

Mark Showalter

Rick Binzel

Francesca Demeo

Petr A Pravec

: Ceux De L'oca

Paolo Morby

Aurélien Tanga

Seth Crida

Federica Jacobson

Michiel Spoto

Patrick Lambrechts

Jean-Pierre Michel

Stefan Rivet

Ast

Kaled Ali

Et

Ana Lucía

Amelia Luchi

Enrique Ainsi Qu'à Mon Cher

l'accueil de

Keywords: minor planets, asteroids, properties, asteroids techniques, spectra, taxonomy iii astéroïdes, propietes, spectra, taxonomie vi asteroides, propiedades, espectros, taxonomía viii

En premier lieu, ma profonde reconnaissance va à mes directeurs de thèse, qui ont oeuvré à ce que ce travail doctoral arrive à bon port : A Benoît Carry, pour son appui constant, pour sa patience, sa générosité et sa motivation, pour m'avoir toujours guidée, partageant avec moi son enthousiasme et son immense connaissance sur les astéroïdes (et plus encore), et à Mirel Birlan, qui avec gentillesse et patience, m'a aussi guidée dans ce monde, particulièrement pour l'obtention de données spectrales, leur traitement et analyse; et qui, quand il me voyait perdre espoir avait toujours une solution en main pour me redonner du courage: nici o problemǎ.

Je remercie aussi Frédéric Vachier et Jérôme Berthier, qui généreusement m'ont aidée et entraîné pendant ces années avec les observations et programmes pour obtenir la précieuse information dont j'avais besoin pour mon travail et qui en plus m'ont accueillie dans leur bureau en me faisant sentir comme à la maison. J'ai eu la chance de les avoir à mes côtés. J'espère que nous aurons l'ocassion de poursuivre notre collaboration pendant longtemps.

List of Figures

gential to spectral curve of spectrum obtained after merging visible spectrum [START_REF] Lazzarin | Visible and near-infrared spectroscopic investigation of near-Earth objects at ESO: first results[END_REF] and NIR spectrum of (88710) 2001 SL 9 . Middle Wavelength position of the centers of the two absorption bands. The regions enclosed correspond to the band centers computed for the H, L, and LL chondrites. Bottom Band area ratio (BAR) versus band I center. The regions enclosed by continuous lines correspond to the values computed for basaltic achondrites (BA), ordinary chondrites (OC), and olivine-rich meteorites (Ol) [START_REF] Gaffey | Mineralogical variations within the S-type asteroid class[END_REF]. . . . . . . 3.8 Plot of binaries with known taxonomy (light green dots), and all-binary population (black dots) among the total asteroid population on the background. . . . 3.9 SMASS binaries colaboration spectra . . . . . . . . . . . . . . . . . . . . . . . . . Some 4.6 billion years ago, the Solar System was forming from the dust and gas left by dead stars, that formed a planetary nebula with diverse composition, that transformed in a distribution of matter with different type of content and a thermal gradient (Fig. 1.1)1 that depended on a star: the Sun. The seeds that later became planets and moons, and the world as we know it, had transformed due to different processes from that initial "debris". We know that because astronomy has the tools that permit us to unveil the mysteries of asteroids and comets, which are some relatively unchanged remnant debris from the formation of the solar system. How did all that occur? Like detectives, we can look and see in what we have in our near cosmic neighborhood, in that rocks of different sizes that orbits our Sun: in asteroids.

What we can see now is what has survived. But all of this debris has experienced numerous collisional, dynamical, and thermal events that had shaped their present-day physical and orbital properties. The task is to interpret this record by observation, studying meteorites, -which are the chunks of them that had also survived to arrive on Earth-by doing experimentation, and using theoretical models to understand how all this happened. The total mass of asteroids is ∼ 1/15 that of the Moon. But even though this represents a tiny fraction of the total mass of planets, their large numbers, their diverse compositions from a variety of materials -mostly rock, some metallic-(Fig. 1.3), and their orbital distributions, provide powerful constraints for planet formation models.

Around ∼ 90% reside in a zone known as the asteroid belt (Fig. 1.2) between Mars and Jupiter, and are strongly influenced by the gravity of the latter. But they are not uniformly distributed through the asteroid belt, there exists certain zones with very few of them, noted by Daniel Kirkwood in 1868. These are gaps in the distances of these bodies orbits from the Sun. Located at positions where their period of revolution about the Sun is an integer fraction of Jupiter orbital period (Fig. 1.20). The inner, middle, and outer sections of the main belt, ranging from 2.0-2.5, 2.5-2.82, and 2.82-3.2 AU 2 respectively, are separated by the 3:1 and 5:2 mean motion Figure 1.1 -Artist's illustration of ǫ Eridani system showing ǫ Eridani b. A Jupiter-mass planet is shown orbiting its parent star at the outside edge of an asteroid belt. In the background can be seen another narrow asteroid or comet belt plus an outermost belt similar in size to our Solar System's Kuiper Belt. The similarity of the structure of this system -the closest debris disk around a star similar to the early Sun-to our Solar System is remarkable. Observations by the NASA Stratospheric Observatory for Infrared Astronomy (SOFIA) confirmed the existence of the asteroid belt adjacent to the orbit of the Jovian planet [START_REF] Su | The Inner 25 au Debris Distribution in the ǫ Eri System[END_REF]. (Credits: NASA/SOFIA/Lynette Cook).

resonances.

We can say that the only constant in the Universe is the change. What we can see now in asteroids is a stage of their evolution. Binary asteroids let us have a deeper insight in that evolution in a shorter time scale.

There has been a long way since the first innocent sights of asteroids. Before, there was no data, astronomers were free to speculate how that might look like. For example the idea that small bodies would not be able to hold on regolith like the Moon does. Wouldn't any impact ejecta just get blasted away, never to return, thanks to the lack of gravity? Nowadays the images of Deimos show that even a 15 km body could retain regolith, even more it seemed that the debris has slid downhill from Deimos' equatorial ridge. "One of the early prejudices was that, in presence of very low gravity, downslope movement wouldn't be effective," As Joseph Veverka said fascinated by what tiny worlds showed "As it turned out, efficiency of moving stuff downhill is independent of gravity" [Small is not Dull, [START_REF] Veverka | Small is NOT Dull: Unravelling the Complexity of Surface Processes on Asteroids, Comets and Small Satellites[END_REF]. The images of these small worlds are now increasing, showing more complexities. What would have thought We are in a golden era for planetary research. Today we have different methods to question nature, a large amount of data, ground and space telescopes, adaptive optics (AO), detectors in the UV, visible, and IR, spacecraft that had already descend on minor bodies and collect samples, plans to impact them, ongoing space missions to asteroids... so even thought we can't test nature like is usual in labs on Earth "controlling" the experiment, we can serendipitously follow objects according to their natural cycles to obtain information.

As Richard Binzel said at ACM 2017 [Advances in Understanding physical properties of small bodies, [START_REF] Binzel | Advances in Understanding physical properties of small bodies[END_REF] the conference on asteroids, comets and meteors, held in Montevideo -Uruguay on April 2017, the study of planetary bodies has moved on a first stage from astronomical to geological, the next stage is to move from geological to geophysical.

1.1. Asteroids Do have satellites on, "Why had God been motivated mathematically to select the planetary orbits in the way He had?". The huge gap between Mars and Jupiter was especially difficult to explain for him. Kepler tried a bold approach placing a new planet between Jupiter and Mars3 [START_REF] Serio | Giuseppe Piazzi and the Discovery of Ceres[END_REF].

The name Asteroids was first used by [START_REF] Herschel | Observations on the Two Lately Discovered Celestial Bodies[END_REF] to denote the star like bodies Ceres and Vesta, after thoroughly observing them, estimating their sizes, and make a digression on the nature of these two stars that were nor planets, nor comets. A new name was needed. Herschel asked for help (urged by the publication of a paper) in between his friends and acquaintances to propose a name for these objects. It was a greek scholar, Charles Burney Jr., who coined the word [START_REF] Cunningham | 211-YEAR-OLD MYSTERY SOLVED: CREATOR OF THE WORD "ASTER-OID" REVEALED[END_REF][START_REF] Cunningham | Early Investigations of Ceres and the Discovery of Pallas[END_REF].

Interestingly, [START_REF] Herschel | Observations on the Two Lately Discovered Celestial Bodies[END_REF] himself had also search for satellites around these asteroids, and conclude "...there can be no great reason to expect that they should have any satellites. The little quantity of matter they contain, would hardly be adequate to the retention of a secondary body...".

In 1901, Charles Andre suggested that the lightcurve of Eros had imprints of a satellite around it. In the 70's, anomalous lightcurves suggested satellites; in the 80's several observations supported the idea that binary asteroids existed: from observing asteroids with slow and fast rotation and the image of double craters on the Moon and even on the Earth. Several efforts were done searching for them without success. More and more lightcurves were acquired from different asteroids with no positive result (Nysa, Ophelia, Hebe, Pallas, etc) [START_REF] Weidenschilling | Do asteroids have satellites? Asteroids II[END_REF], 1987[START_REF] Gehrels | The absence of satellites of asteroids[END_REF].

It was not until 1993 that, on its tour to the jovian system, the Galileo spacecraft made the first detection of a satellite around an asteroid, in a rather serendipitous way. The images taken by the probe showed that (243) Ida (31km), has a moon, [Belton and Carlson, 1994] (Fig. 1.5) officially named Dactyl (1.4km) now. That event boosted the observational search and theoretical research on binary asteroids, including numerical simulations to understand the processes that could form such systems.

The first detections from lightcurves shapes of Near Earth Asteroids (NEAs) were made by Petr Pravec et al. and Stefano Mottola et al., these includes: 1994 AW 1 [START_REF] Pravec | Two-Period Lightcurve of 1994 AW 1 : Indication of a Binary Asteroid[END_REF], 1991 VH [START_REF] Pravec | Occultation/Eclipse Events in Binary Asteroid[END_REF], 3671 Dionysus [Mottola et al., 1997], and 1996 FG 3 [START_REF] Pravec | FG_3[END_REF].

The first confirmed detection of an asteroid satellite from a ground-based telescope was that of Petit-Prince (13km), the moon of (45) Eugenia (215km) by direct imaging assisted by adaptive optics (AO) in 1998 [Merline et al., 1999]. This was the first positive detection from a dedicated survey with the capability to search for faint companions (∆m ∼ 7 mag) as close as a few tenths of an arcsecond from the primary. With this survey were also detected the binaries: (762) Pulcova and (90) Antiope [START_REF] Merline | Discovery of Companions to Asteroids 762 Pulcova and 90 Antiope by Direct Imaging[END_REF].

Why study binary asteroids?

are massive enough, they don't become differentiate bodies. Their evolution is determined by its environment. Things happen when they approach a planet, when there is a collision, or because of the solar wind or when interplanetary particles impinge on them. As such, they evolve differently from planets and being in a way pristine, carry with them the imprints of their birth from the solar nebula, this is why they can serve as tracers of the evolution of the Solar System.

Asteroids, -and mostly binary asteroids-can give us a window of the processes involved in the evolution of the Solar System and a time-scale that shows how the composition of the Solar System was varying with time.

The scope of this manuscript will be dedicated to binary asteroids in the inner regions of the Solar System, the Kuiper belt population that apparently have different physical, dynamical and evolutionary properties, will not be considered here. In general, I will refer to binaries, but in fact the population I am considering includes triples like (45) Eugenia, and (87) Sylvia.

Binaries can also help to constrain our knowledge of the collisional evolution of asteroids.

On designation of asteroids and binaries

At the beginning, asteroids were unique objects, they were given names of notable personages: Ceres, Pallas, Juno, Vesta 4 , etc. But, little by little and then, abruptly the frequency of discoveries began to grow and boost and it was needed a more suitable way to name them. Currently, an asteroid is given a provisional designation with four numbers, 2 capital letters, and a subscript number related to its discovery, composed in this way: first four numbers are the year of discovery, then the first letter is the half-month period during which the object was discovered, the second letter with a subscript number gives the order of discovery within that period. For example: the binary 1991 RJ 2 was discovered in 1992 in the first fortnight of September 5 .

When the orbit of the asteroid becomes well enough determined, the asteroid receives a permanent number issued sequentially by the Minor Planet Center. On the other hand, names for minor bodies like asteroids can be proposed to the Committee on Small Body Nomenclature (CSBN) of the IAU http://www.ss.astro.umd.edu/IAU/csbn/, the one who will decide according to several rules6 .

In the case of binaries, when one satellite is discovered, a provisional name is also given, the letter code is replaced by the asteroid number in parentheses. For example, the satellite of (45) Eugenia was named S/1998 (45) 1, being 1998 the year of the moon discovery, the discoverers Chapter 1. Introduction proposed Petit Prince7 as permanent name for this satellite, which was accepted. In 2004, a second satellite was discovered, it still has a provisional name, S/2004 (45) 1, but it's informally well known as Petit Princesse. Where more than one moon has been discovered, the discovery sequence is specified by roman numerals, so that Eugenia's moon would be: (45) Eugenia I Petit Prince, and (45) Eugenia II Petit Princesse.

The discovery of new binaries has been increased as technology and methods improved. Although the techniques used defines also biases on the knowledge of binaries population. Lightcurves permits the detection of close satellites around small asteroids, not of distant companions. With radar, satellites widely separated from the asteroid can be detected, but there is a limit for the detection for distant MBAs. High resolution imaging is suitable for finding distant companions of large MBAs.

The reports on discovery of asteroid satellites are sent to the Central Bureau for Astronomical Telegrams (CBAT) which is responsible for the dissemination of information on transient astronomical events. Confirmed discoveries are published as "telegrams" by CBET (Central Bureau Electronic Telegrams) 8 and can be consulted at the Satellites and Companions of Minor Planets page of the IAU9 .

There exists dedicated programs for the discovery of satellites like, Petr Pravec's group Ondrejov Asteroid Photometry Project10 , Raoul Behrend Light curves program 11 .

Dedicated decadal publication on Asteroids (Asteroids, Asteroids II, Asteroids III, Asteroids IV) by University of Arizona Press refer from the first volume to the possibility, and then when confirmed, to the existence of binary asteroids.

It also exist Binaries Asteroid's Workshop (the first one celebrated in 2007, the last one -4th-in 2016) where specialists gather to discuss ideas on detection, characterization, formation, and implications of binary and multiple objects among the NEO, main-belt, Trojan, Centaur and TNO populations.

Nomenclature

The scenario of binaries is a bit diverse, some definitions to clear the panorama, according to [START_REF] Jacobson | Dynamics of rotationally fissioned asteroids: Source of observed small asteroid systems[END_REF], [START_REF] Walsh | Formation and Evolution of Binary Asteroids[END_REF] are useful to group them in order to define better the objects of this work.

• Binary asteroids: A couple of asteroids that are gravitationally bound are called binaries (in case they are three they are known as triples). The larger component is the primary, 1.2. Why study binary asteroids? • Asteroid Pairs: These denote a couple of asteroids that are genetically related but not gravitationally bound. Recently was discovered the youngest pair P/2016 J1. Remarkably, each member went active after splitting [START_REF] Moreno | The Splitting of Double-component Active Asteroid P/2016 J1 (PANSTARRS)[END_REF].

• Contact Binaries: These are two asteroids in contact that look as a double-lobed object.

As for today, there are a handful of confirmed contact binaries like 2014 JO 25 (which just happen to pass close to the Earth on April 19 of this year, Fig. 1.6), and several suspected. On the other hand, comets like 67P/Churyumov-Gerasimenko and 8P/Tuttle are contact binaries.

• Split Pairs: These systems are inferred from dynamical models having their heliocentric orbits closely link but they are not actual binaries, although some of its members are binaries.

On the size of binary asteroids

At the beginning, asteroids had been considered to be spherical, since the first spacecrafts like NEAR sent the images of (433) Eros it was first viewed how different from round can asteroids be. This complicates the determination of the volume, and with that the density. It is necessary to determine as accurate as possible the volume. Several techniques can be used for that.

Why study binary asteroids?

Infrared light is widely used to determine an asteroid's size because visible-light from the sun reflects off the surface of the rocks. The more reflective the object is, or the more albedo the object has, the more light it will reflect as can be see in Fig. 1.8, three asteroids doesn't look the same in both ranges of wavelengths. that means that the brightness of an asteroid in visible light is the result of both its albedo and size. Combined measurements in visible and infrared light are used to calculate asteroids albedos.

Figure 1.8 -Size of an asteroid from optical and infrared observations. (Credit: NASA)

Small and large asteroids behave differently. That is why in general they are divided in small and large, the dividing line is approximately set by [START_REF] Jacobson | Effect of rotational disruption on the size-frequency distribution of the Main Belt asteroid population[END_REF] to a diameter of about 20 km. The small ones are affected by the YORP effect (non gravitational effect) along their lifetime (Fig. 1.7). For low sizes, very small asteroids are defined as asteroids with diameters less than 200 m. (Fig. 1.9). Among small asteroid about 15 ± 4% are binary asteroids [START_REF] Margot | Asteroid Systems: Binaries, Triples, and Pairs[END_REF]. We currently know 213 systems.

Chapter 1. Introduction

This apparent lower abundance of binaries with larger primaries/satellites might be related with mechanism preferring creation/stability of satellites among asteroids with Dp < 2 km, or there is a mechanism that limits secondary size to Ds < 1 km.

Figure 1.9 -Composite image showing the comparative sizes of nine asteroids from Vesta (∼530 km) to Itokawa (∼0.5 km). Image from NASA.

Smaller sizes typically indicate a younger surface age, so it is possible the difference is due to weathering effects. In general, the characterization of asteroids is biased to large or interesting cases due to the resources implied in their observation.

1.2.3

Where are the binaries in the Solar System?

Asteroids are not homogeneously distributed in the Solar System as can be seen in Fig. 1.2, there are denser regions. The crowded zones were defined by different type of interactions and are a snapshot in the evolution of the Solar System.

Dynamically, asteroids are grouped in the following populations (Fig. 1.11):

• NEAs the Near Earth Asteroids are the asteroids with perihelion distance q less than 1.3 AU. This group is subdivided according to their perihelion distance q, aphelion distance

Q (Q = a(1 + e))
and their semi-major axes a12 .

-Atiras are those whose orbits are contained entirely within the orbit of the Earth Q< 0.983 AU (named after asteroid 163693 Atira).

Why study binary asteroids?

-Atens are Earth-crossing NEAs with semi-major axes smaller than Earth's and Q>0.983 AU (named after asteroid 2062 Aten).

-Apollos are Earth-crossing NEAs with semi-major axes larger than Earth's (named after asteroid 1862 Apollo) and q<1.017 AU.

-Amors are Earth-approaching NEAs with orbits exterior to Earth's a> 1AU, but interior to Mars 1.017<q<1.3 AU (named after asteroid 1221 Amor).

-PHAs the Potentially Hazardous Asteriods are NEAs whose Minimum Orbit Intersection Distance (MOID) with the Earth is 0.05 AU or less, and whose absolute magnitude H is 22.0 or brighter. In principle these could possibly impact the Earth within the next century, producing major damage. About 1800 PHAs are known as for 14 May 2017 from an estimation of 4700±150013 (Fig. 1.12).

• Mars Crossers these asteroids have an orbit that crosses the orbit of Mars. Due to secular perturbations, Mars eccentricity varies substantially over million-year time scales; thus, this population fluctuates over time.

• MBA the Main Belt Asteroids occupy the Main asteroid belt between Mars and Jupiter 2.2 <q< 3.3 AU (the most asteroid-populated zone in the Solar System). These asteroids are grouped according to their orbits as: Hungarias (HUN), Inner Main Belt (IMB), Middle Main Belt (MMB), Outer Main Belt (OMB), Cybeles, and Hildas.

• Jupiter Trojans trojans in general are asteroids that have stable orbits in the L 4 and L 5 Lagrangian points of a planet, in this case, Jupiter. They share Jupiter's orbit at 5.2 AU but lead or trail the giant by ∼60 • in longitude.

• TNOs Trans Neptunian Objects, actually not considered asteroids, but included in the list for completion.

There are binary asteroids all over in the Solar System! The last census 14 gives:

• 61 near-Earth asteroids (2 with two satellites each),

• 22 Mars crossing asteroids (1 with two satellites),

• 128 main-belt asteroids (8 with two satellites each),

• 4 Jupiter Trojans

• 81 Trans-Neptunian Objects (TNO)

Clues can be obtained from binary asteroids prevalence in a population. As noted by [START_REF] Polishook | Photometry of Aten asteroids-More than a handful of binaries[END_REF], binarity is a very common phenomenon for NEAs, specially for

Chapter 1. Introduction

Atens, perhaps even more than for other NEA groups among which 15% are assumed to be binaries [START_REF] Bottke | Binary Asteroids and the Formation of Doublet Craters[END_REF]. This may indicate that Atens suffer more disruptions caused by planetary encounters than do Apollos or Amors. One possible explanation could be their higher likelihood of tidal interactions with Earth and Venus, causing stronger tidal forces.

According to numerical models by [START_REF] Scheeres | Regolith Mechanics on Binary Asteroids[END_REF] Aten asteroids are more prone to spin up and three times more likely to disrupt than Apollo and Amor asteroids. Another possibility is that the much closer distance of small Atens to the Sun enhances the effect of thermal reemission due to the YORP effect. Thus, the Atens can rotate faster and could eventually disrupt.

In this work I will concentrate in binaries in the internal part of the Solar System (Fig. 1.13), but I also have observed TNOs (Ch. 4).

Asteroids in the main belt were thought to have formed essentially where they are now [START_REF] Gradie | Compositional structure of the asteroid belt[END_REF]. Early measurements in the 80's showed that the inner main belt was redder and the outer main belt was bluer. Distinct color groupings of asteroid types group were found, the difference seemed a function of distance from the Sun. At the time, that was interpreted as the remanent of the temperature gradient across the Main Belt from the time of planetesimal formation, supporting the idea of a static Solar System. But that idea has changed dramatically, now we know there has been many variations and a lot of mixing, the main belt of asteroid and the Kuiper Belt-are no longer considered primordial.

Planetary migration models like Nice Model [START_REF] Tsiganis | Origin of the orbital architecture of the giant planets of the Solar System[END_REF], Gomes et al., 2005, Morbidelli et al., 2005[START_REF] Levison | Late Orbital Instabilities in the Outer Planets Induced by Interaction with a Self-gravitating Planetesimal Disk[END_REF] and Grand Tack Model [START_REF] Walsh | A low mass for Mars from Jupiter's early gas-driven migration[END_REF] recreate the structure of the Solar System (Fig. 1.14). Late-stage migration modeled by [START_REF] Levison | Contamination of the asteroid belt by primordial trans-Neptunian objects[END_REF] helps to support a Dynamic Solar System. With the measure of the composition predicted by [START_REF] Levison | Contamination of the asteroid belt by primordial trans-Neptunian objects[END_REF] we can see now that the mixing is the norm in the MBA [DeMeo and Carry, 2013].

Formation mechanisms of binary asteroids

Formation mechanisms of binary asteroids

One of the remarkable aspects of binaries is their diversity (Fig. 1.7). When studying them, we are decoding the differences in their formation and evolution mechanisms that act as a function of size, distance from the Sun, and the properties of their nebular environment at the beginning of Solar System history and their dynamical environment over the next 4.5 billions of years. Binaries are the laboratory where we can study numerous types of physical processes acting on asteroids, testing physical properties otherwise possible only with spacecraft. Several scenarios are considered for the formation of binaries.

Mutual Capture

In this scenario, the two components of the binary system become mutually bound by virtue of having relative speeds at encounter below their mutual escape speeds. This is a possible origin of Mars moons Phobos and Deimos (still an open question). Escape speeds of asteroids are of order m/s, while encounter speeds are of order km/s [START_REF] Bottke | Velocity distributions among colliding asteroids[END_REF]. The chances of direct capture are really small in the present-day populations of these bodies. However if a third body is present within the Hill sphere, the encounter speed can be reduced, allowing the capture [START_REF] Goldreich | Formation of Kuiper-belt binaries by dynamical friction and three-body encounters[END_REF].

It must be considered that given the short dynamical lifetime of NEAs and the relatively short collisional lifetime of MBAs, the mutual capture mechanism is not favored for those groups (any binaries formed in this fashion have long been destroyed).

Collisions

Since collisions are the dominant evolutionary process affecting asteroids, it is plausible that these satellites are by-products of cratering and/or catastrophic disruption events.

If a close encounter between two minor planets results in a collision, binaries may be formed by virtue of interactions between the debris pieces and/or between the debris and the largest remnant [START_REF] Scheeres | Stability of Binary Asteroids[END_REF]. Following Newton's laws, material ejected from the surface of a spherical body either escapes, reimpacts, or enters orbit.

There are implications of the system transferring energy and angular momentum between rotational and translational motion, while conserving the total system energy and angular momentum. From results [START_REF] Scheeres | Stability of Binary Asteroids[END_REF] developed a set of sufficient conditions for stability against escape and impact. With these he delineate several classes of final outcomes for a binary asteroid system, each of which may have implications for asteroid observations. [START_REF] Durda | The formation of asteroid satellites in large impacts: results from numerical simulations[END_REF] performed numerical simulations of impacts with smooth-particle hydrodynamics considering the formation of SMAshed Target Satellite (SMATS, Fig. 1.15). which applies for large asteroids like Camilla (Ch. 5).

Chapter 1. Introduction

Families of asteroids are also formed from collisional events, their study gives us information on the physics of catastrophic collisional breakup. The family members are the outcome of an experiment that was performed by nature.

Figure 1.15 -Satellites resulting from large impacts according to simulations by [START_REF] Durda | The formation of asteroid satellites in large impacts: results from numerical simulations[END_REF]. SMAshed Target Satellites (SMATS) form from impact debris that enters into orbit around the remaining target body, which is a gravitationally reaccreted rubble pile (Fig. 1.18). Smaller escaping fragments with similar trajectories become gravitationally bound to one another.

Tidal Breakup

After having observed that 10% of the impact craters on Venus and Earth (Fig. 1.17) are doublets (simultaneous formation) and with the use of numerical models, Bottke and Melosh [1996a,b] proposed that some fast rotating rubble-pile contact binary asteroids15 (Fig. 1.18), undergo tidal breakup (they were well separated before impact) and split into multiple coorbiting fragments after experiencing a close approach with a planet, in similar way as comet Shoemaker-Levy 9 fragmented as it passed by Jupiter before crashing on the planet [START_REF] Asphaug | Density of comet Shoemaker-Levy 9 deduced by modelling breakup of the parent 'rubble pile[END_REF](Fig. 1.16). This mechanism may cause the binary component to escape,

Properties of binary asteroids

but secondary satellites may form continuously during close encounters. This determines a steady-state distribution of binary asteroids in the Near Earth region.

Figure 1.16 -Shoemaker Leavy-9 comet breakup

Rotational Disruption

The median dynamical lifetime of NEAs (before ejection from the Solar System or collision with a planet or the Sun) is ∼10 Myr [START_REF] Gladman | Dynamical lifetimes of objects injected into asteroid belt resonances[END_REF]]. There must be some efficient mechanism that can form binaries operating presently in the NEA region. A rotational disruption mechanism such as tidal disruption may be viable for the formation of binary NEAs. This requires that the progenitor have low tensile strength, i.e. that the object cannot resist being stretched (such as by centrifugal forces). [START_REF] Richardson | Gravitational Aggregates: Evidence and Evolution[END_REF] describe the evidence for the existence in the minor planet population of these so-called gravitational aggregates (of which "rubble piles" are a special case of loosely consolidated bodies with very low tensile strength and moderate porosity). The low bulk densities of primitive asteroids, many of which were measured by virtue of a natural satellite, are suggestive of this kind of interiors: Bulk porosities of 40%-60% are required if such bodies are the parent bodies of chondritic material that falls to Earth in the form of meteorites. It is currently thought that most binaries with D<20km were formed by rotational fission because of their short rotation periods [START_REF] Margot | Asteroid Systems: Binaries, Triples, and Pairs[END_REF].

Properties of binary asteroids 1.4.1 Orbital elements

The keplerian elements that define the orbit of an asteroid are (Fig. 1.19):

• a semimajor axis 1/2 of the major axis of the elliptical orbit (the mean distance from the Sun). Describes the dimensions of its orbit around the Sun, its value determine its orbit period T . NEAs, it is even predicted spin-state changes for (99942) Apophis after its close encounter with Earth on 2029 [START_REF] Scheeres | Abrupt alteration of Asteroid 2004 MN4's spin state during its 2029 Earth flyby[END_REF].

Asteroids with diameters larger than ∼ 200 m rarely spin with periods less than ∼ 2.2 h, which corresponds with the critical disruption spin rate of self-gravitating, "rubble pile" bodies [Pravec and Harris, 2007], a possible mechanism of formation of binaries.

The majority of NEA binary systems are found with a rapidly rotating primary, with rotation periods between 2.2 and 3.6 h, which are among the most rapid rotations found for NEAs [START_REF] Pravec | Photometric survey of binary near-Earth asteroids[END_REF], this supports the theory for formation of small binaries by rotational fission.

Unfortunately, currently no clear test exists to help differentiate between the lightcurve of an elongated asteroid to a lightcurve of a synchronous binary asteroid. [START_REF] Ďurech | Photometric signatures of highly nonconvex and binary asteroids[END_REF] showed that contact binaries or near contact binaries can be modeled as single bodies with almost the same lightcurves. Asteroids that were suspected as binaries, such as (216) Kleopatra, exhibit their true bifurcated-elongated shape only by radar and high angular resolution observations [Ostro et al., 2000] and asteroids that were considered as an elongated asteroid, such as (90) Antiope, were found to be binaries using direct imaging with high angular resolution observations. Moreover, the features in the asteroid's lightcurve, that support the binary scenario depend on observation geometry: the amplitude of the lightcurve is changing with increasing phase angle, The shape of the curve (V-shaped minima/U-shaped maxima) change with the aspect angle of the asteroid rotation axes.

From photometry of Atens asteroids throughout the Solar System were discovered as binaries:

1.4. Properties of binary asteroids (69230) Hermes, a NEA with rotation and orbital periods of 13.89 h [START_REF] Pravec | UB (Hermes)[END_REF];

(854) Frostia, (1089) Tama, (1313) Berna and (4492) Debussy are main belt asteroids with periods of 37.73, 16.44, 25.46 and 26.61 h, respectively [Behrend et al., 2006]; (90) Antiope is an almost-synchronous binary system of equal-size components.

Angular momentum content

The angular momentum is a fundamental characteristic of asteroid rotation. Both the angular momentum vector L and the inertia tensor Î changes during the evolution of asteroids through collisions and other processes, L is defined as: L = Î ω were ω is the spin angular velocity of the asteroid. The total angular momentum in a binary asteroid is:

L = L 1 + L 2 + L or b (1.1)
where L i is the rotational angular momentum of the i th body and L or b is the orbital angular momentum. Pravec and Harris [2007] considered the ratio between the mass equivalent sphere total angular momentum of the system and the angular momentum of a critically spinning equivalent sphere 16 . The angular momentum of the equivalent sphere spinning at the critical spin rate is L eq sph . The normalized total angular momentum of the binary system is expressed as:

α L ≡ L 1 + L 2 + L or b L eq sph (1.2)
Applying the above considerations to a data set of binaries, Pravec and Harris [2007] obtained the angular momentum content in binaries. They found that small asteroid binaries have the total angular momentum close to critical. For systems originating from critically spinning rubble piles, e.g., by a spin fission, α L is close to 1. This suggests that the small binaries formed from parent bodies spinning at the critical rate (sufficient to overcome gravity) (Fig. 1.23).

Mass and Bulk Density

The determination of the mass of an asteroid is not a trivial task. One of the ways this can be done is by means of gravitational perturbation: (on a natural or artificial body) asteroidasteroid or asteroid-spacecraft. This can be done from determining the trajectory of the perturbed body after the close encounter. Needless to say that this kind of encounters are scarce, in the first case ruled by nature and the second by budget, although nowadays with past Chapter 1. Introduction and current missions flybys and rendezvous has been more frequent, and now even asteroid dedicated.

Other gravitational perturbation is the one that is produced from the interaction between an asteroid and its satellite which is what we consider in the binaries of this manuscript. By means of Kepler's third law [deduced from observations [START_REF] Kepler | appendix habet comparationem huius operis cum harmonices Cl[END_REF], it can be determined the mass of the primary body knowing the orbital period P and the semimajor axis of the satellite:

P 2 a 3 = 4π 2 G M (1.3)
with M the mass of the system (mass of primary and secondary) M = M p + M s and a the mean separation of the bodies (orbital semimajor axis), where the components are considered as point masses and G is the gravitational constant.

The first determination of this kind came of course from the first confirmed satellite of an asteroid: Dactyl, the satellite of (243) Ida. From spatially resolved images taken by the Galileo spacecraft of this binary [START_REF] Belton | Bulk density of asteroid 243 Ida from the orbit of its satellite Dactyl[END_REF] were able to estimate the mass, volume and bulk density of Ida.

In principle, measuring any two of the quantities yields the third; generally, P and a are obtained from observations, and M is deduced. To obtain masses of the individual components requires an assumption that either M p ≫ M s (so that M ≃ M p ), or, if reliable estimates of the sizes of either component are available, that they have the same bulk density which is what is generally assumed (although may not be necessarily true). Measured sizes and masses may be combined to estimate the density (ρ, the mass per unit volume of a substance), a fundamental property indicative of composition (see [START_REF] Carry | Density of asteroids[END_REF] for an extensive study).

Grain density is the mass of an object divided by the volume occupied by a grain. On the other hand, the term bulk density is referred to the mass of an object divided by its total volume. It is the density measured by spacecrafts.

The porosity is the ratio between grain and bulk density and it gives the percentage of the bulk volume of a solid occupied by empty space. It is the non solid or pore volume fraction and as such, dimensionless. The porosity may also be inferred if a likely analog material (such as a meteorite with similar spectral signatures to an asteroidal component) with known bulk density is available this can provide a clue to the internal structure, such as whether large void spaces may be present [START_REF] Consolmagno | The significance of meteorite density and porosity[END_REF].

Most asteroids have significant porosity. This property can be large enough to affect the internal structure of asteroids, their gravity field, impact dynamics, collisional lifetimes. It also can affect their physical properties which include thermal diffusivity, seismic velocity, cosmic 1.4. Properties of binary asteroids ray exposure and dielectric permeability. Thermal and seismic effects can affect asteroid internal evolution, metamorphism, shock dissipation and elastic properties which in turn can determine whether colliding asteroids accrete or disrupt [START_REF] Britt | Asteroid Density, Porosity, and Structure. Asteroids III[END_REF].

High porosity attenuates shock propagation, affecting the nature of cratering and lengthening the collisional lifetimes of porous asteroids. From density trends analysis, asteroids are divided in 3 groups:

1. monolithic asteroids 2. asteroids with macroporosities

rubble piles

In case of collisions, it has been discovered by experiments and porosity models that porosity helps to dissipate a portion of the impact energy into the crushing of pores, which result in compaction. As such, porous asteroids are more resistant to collisional disruption.

Comparing masses of asteroids, Ceres has over one-third of the estimated total mass of all the asteroids in the asteroid belt. [START_REF] Kuchynka | A new approach to determining asteroid masses from planetary range measurements[END_REF] estimate asteroid masses from planetary range measurements. The mass of the Main Belt of Asteroids is estimated in 30 ×10 20 kg [START_REF] Kuchynka | A new approach to determining asteroid masses from planetary range measurements[END_REF].

Surface Properties

The reflectivity of the light on an asteroid depends on the light impinged, the composition of the surface, and the size of the grain on the surface.

Because of continuous bombardment of ions from solar wind and interplanetary particles, atmosphereless and magnetosphereless bodies like asteroids are exposed to these fluxes.

Meteorites are samples of planetary bodies that have survived passage through our atmosphere and reached the Earth, as such, they are cosmochemical time capsules from the Solar System's birth, encoding clues about how our cosmic neighborhood came to be. Coming mainly from asteroids, they serve as evidence of the nature of these bodies. This gives us clues about composition, bulk density and porosity of their parent bodies. Identification has been made for the Moon, Mars, Vesta [START_REF] Prettyman | Elemental Mapping by Dawn Reveals Exogenic H in Vesta's Regolith[END_REF], and Itokawa [START_REF] Nakamura | Itokawa Dust Particles: A Direct Link Between S-Type Asteroids and Ordinary Chondrites[END_REF].

But in meteorite collections there is not yet positive identification of all asteroid types, there are some missing meteorite to link with all the parent bodies known at the moment so we can piece together the full picture. There are several international efforts to recover fresh meteorites short after they arrive on Earth. Networks with cameras and radars are surveying the sky in order to detect meteors and put alerts so meteorite recovery can be organized. Some of the networks are: FRIPON (France), Australia, The NASA All-sky Fireball Network, Saskatchewan Fireball Camera Network (USA), Brasil etc.

Chapter 1. Introduction

Part of the aims of this work was to assess the taxonomy of binary asteroids with unknown spectral classification to determine their composition for the first time (Ch.3). The characterization of binaries physical properties from the ground is possible by spectroscopy in both visible and infrared spectral regions. When possible, mineralogical composition can be established.

Experiences in labs explain the spectral differences observed between the most populated class of meteorite the ordinary chondrites OC and the surface of their supposed parent bodies (S-type asteroids). It has been simulated in labs the ionic bombardment of ion fluxes.

Absolute Magnitude and Albedo

The absolute magnitude of an asteroid H , is a measure of its intrinsic mean brightness in the visual if the asteroid were placed at a distance of 1 AU from Earth, at 1 AU from the Sun, and at zero phase angle. This is estimated from measurements of its apparent magnitudes at the occasions it has been observed, meaning that it had different configurations: heliocentric distance, phase angles and aspect, although in first approximation that last quantity is assumed to be spherical.

Methods to study asteroids

Basically all the information we have from asteroids come in form of light, to collect it we use detectors in telescopes. In our era we have them on ground and also in space. We can detect also signals from different ranges of wavelength namely UV, visible, IR and radio. In this work we will use only visible and near Infrared (NIR) that at the end give complimentary information.

Regarding telescopes, although size matters, actually there's a wide variety of telescopes that observers uses to collaborate with the aims to better determine the nature of asteroids.

From amateur "little" telescopes gathering light for lightcurves (LC) and occultations, to the biggest ones in super professional observatories that include AO and state of the art optics and mechanics and even space telescopes and space probes with sensitive instruments.

The detection of light from asteroids comes from different programs, which includes large surveys that were originally planned to detect other sources like stars, galaxies and cosmological objects, were it happens to pass by some of these minor bodies in the Field of View, the detection is serendipitously made.

"We are now on the threshold of a new era of asteroid studies," wrote Tom Gehrels in the introduction of Physical studies of minor planets, [START_REF] Gehrels | Physical studies of minor planets[END_REF] 17 having at the time the completion to magnitude ∼14, and detected magnitude 16 in extended program. Since then,

Methods to study asteroids

the work done on asteroids has come a long way, now magnitudes reach ∼20-24.

Lightcurves

Photometric observations are the classical method for obtaining information on objects with a complex shape and structure. Lightcurves are one of the most fruitful and classical methods to discover and characterize binaries. It consists in gathering light from astronomical objects, following them as to see the differences in the amount of light received. From that light record, one can confirm if some asteroid is not single by the different peaks in the lightcurve, it serves also to determine the periods of each component and their poles [START_REF] Pravec | Binary asteroid population. 3. Secondary rotations and elongations[END_REF] (Fig. 1.21). Due to eclipses and the mutual occultations of components, the amplitude of the light curve of the asteroid can change. In order to find specific features, it is necessary to perform photometric observations over a long time interval which depends on the particular system. modest equipment (depending on the magnitude of star and asteroid). For this reason there are several groups dedicated to observe occultations, many of them, amateur astronomers, some of which had made valuable contributions to the knowledge of asteroids. In fact, occultations, alike asteroid lightcurve detections, gives opportunity for collaboration between professional and amateur astronomers, something that is happening more often nowadays.

For each detection, the time of the occultation can be converted in a distance called chord. Only one of these chords is not enough, the more chords the better, the more events recorded for the same object, the better, because this allows to constrain the shapes of asteroids (Fig. 1.25). For this reason, when an occultation is known to happen, alerts are diffused and observation campaigns organized in order to involve and display observers over the predicted path of the shadow that will be projected on the earth by the passage of the asteroid in front of the star. That shadow will move quickly, at ∼ 30000 km/h, meaning that for the observers, a typical event can be of only several seconds (depending on the size of the asteroid).

By the reliable registration of the time of the beginning and end of the occultation by each observer, it will be possible to rebuild the profile of the asteroid (for the plane projected on the earth) and estimate it dimensions. Occultations lightcurve profiles have allowed to detect atmospheres, and even the first system of rings around centaur Chariklo [START_REF] Braga-Ribas | A ring system detected around the Centaur (10199) Chariklo[END_REF]). In the case of binary asteroids, with the predicted path of the shadow from ephemeris of the asteroid and the star to be occulted, it is possible to determine information of satellite, a very difficult task by other means. In this Gaia era, more precise ephemeris are beginning to be released, this will evidently boost the detection of occultations [START_REF] Tanga | Asteroid occultations today and tomorrow: toward the GAIA era[END_REF].

Spectroscopy

Astronomy became physics when at last the composition of the first celestial bodies were revealed through spectroscopy, this began with the first spectroscope invented by Joseph Fraunhofer in 1814. Since then, the advance in knowledge of composition of bodies has improve hand in hand with better instruments, techniques, and methods. In the case of asteroids, that reflect light, it is performed reflectance spectroscopy in the visible and NIR for this work.

Other methods

Radar

Radar is a suitable technique for objetcs close to the Earth. Although some Main Belt asteroids have been observed there are not many suitable MBAs targets because the SNRs are much lower than for NEAs (echo power goes as distance to the power -4).

Radar is suitable to detect the surface structure of asteroids on grain size scales which can be deduced from the variation of reflectivity with phase angle. Radar provide knowledge about the size, shape, metal content, and surface roughness of asteroids.

The highest resolution that can be achieved is 3.75 m/pixel. Radar observations benefit greatly from optical observations, especially lightcurves and taxonomic classification.

Radar observations provide unambiguous detections of binary asteroids because images at decameter resolution can resolve the individual components.

Polarimetry

Polarimetry can be used to define the diameter, albedo, compositional class and surface structure of an asteroid. This measurement depends on the variation of linear polarization of the sunlight reflected from the asteroid with phase angle. The plot of polarization as a function of the phase angle defines the curve of polarization of an asteroid, which is negative at small angles and rise linearly at angles greater than 15 • . The inversion angle is where the polarization changes sign. It is known an experimental relationship between the albedo and the slope of the polarimetric curve at the inversion angle (Fig. 1.26).

Data & reduction

In this section I will present technical details on instruments for data collection and data treatment.

When detecting light for astronomy, there are several procedures to be performed because the signal must be reliable for research purposes.

Basic Concepts of Photometry

Photometry is a photon-counting technique that gives us information about the brightness of a body, in the case of asteroids, its shape and the scattering properties of its surface. When a time series of brightness measurements are combined, we can have a lightcurve which shows the variations in brightness as the body rotates upon itself and move around the Sun.

The measure of photometric quantities is affected by several effects. This is why images must be corrected.

Photometric sky

This is the best sky for observing astronomic objects: no visible clouds, transparency variations under 2%, only assessable from the analysis of photometric standard stars. Unfortunately, when observing even at large facilities, nothing assures that the weather will be good enough, Luckily, for some not very dim targets, it is possible to work with a clear sky, even with a fraction of the Moon. If relative photometry is performed, the weather is not so stringent, one compares the instrument magnitude of the object to a known comparison object, and then corrects the measurements.

Figure 2.1 -Atmospheric electromagnetic transmittance. Earth atmosphere is transparent to visible light and some radio waves and is absorbing in most parts of the IR. UV, X and gamma rays don't pass through it. Credit: NASA.

Magnitude

For celestial objects, the brightness is referred to as the magnitude, a scheme defined by Hipparchus in 120 BC based on the appearance of stars to the naked eye, with higher numbers indicating fainter objects. Originally it reaches until magnitude 6 (the dimmest seen with the eyes). The scheme is still used nowadays adapted to the observations with instruments and detectors covering negative quantities until magnitudes bigger than 20. But human vision is logarithmic, apparent brightness (flux) and magnitudes are related by the difference in magnitude defined by Norman Pogson in the 1850s.:

m 1 -m 2 ≈ 2.5 log F 2 F 1 (2.1)
where m 1 and m 2 are magnitudes, and F 1 and F 2 are fluxes for two objects.

Magnitude systems

As stated, the definition of magnitude is relative, addressing the magnitude difference between two objects. To be able to compare astronomical sources observed with different telescopes, there is a need to standardize the measure. This is why there are standardized sets of filters An important concept for absolute calibration, is the comparison to standard and field stars.

For moving objects like asteroids, it is also important to correct for the varying heliocentric and geocentric distance, and the phase angle.

Atmospheric Absorption

Depending on the wavelength of light, Earth's atmosphere can be transparent or opaque due to the composition of the atmosphere. Some near infrared (NIR) light can reach observatories on high altitudes. There are infrared (IR) windows centered at certain wavelengths as 1.25. 1.65,2.2,3.5 and 4.8 µm (Fig. 2.1).

Optical Diffraction

The image of a point source of light (like a star) formed by a circular aperture is fundamentally limited by diffraction, which causes a point source of light to be surrounded by a series of bright and dark rings. At a critical angle θ c = 1.22λ/D, where D is the telescope diameter and λ is the wavelength, both in meter. The first dark ring in one object's pattern falls into the central bright spot of the other object's and one can not distinguish the two objects (Fig. 2.2). The angular resolution in radians is

θ θ = λ D (2.2)
Depending on the wavelength, this can be improved with bigger diameters, but diffraction will never disappear.

Seeing and image quality

The seeing is the blurring of the images due to the turbulence in Earth's atmosphere. It is an inherent property of the atmospheric turbulence, independent of the telescope that is observing through the atmosphere.

The image quality, on the other hand, is defined as the full width at half maximum (FWHM) of long-exposure images, is a property of the images obtained in the focal plane of an instrument mounted on a telescope observing through the atmosphere. It is therefore a quantity measured at a certain airmass and wavelength of observation. The image quality in a large telescope is always better than the seeing at the same wavelength and airmass [START_REF] Martinez | On the Difference between Seeing and Image Quality: When the Turbulence Outer Scale Enters the Game[END_REF].

The point spread function, or PSF is the function that describes how the image from a point source is degraded in the focal plane of a telescope due to seeing and optics.

Telescopes

Figure 2.3 -Portable telescope for occultations

Telescopes

I have used myself different telescopes, from mining databases I have collected images of large telescopes some with AO systems, and even one space telescope. I will give a brief description of all of them.

Mobile telescope for stellar occultations

I was trained with a small (D<30cm) commercial telescope for observing occultations. For this it was important to set up the instrument as quickly and efficiently as possible (trained with stopwatch). I learned how to perform the polar alignment as fast as possible, this is the aligning of the mount so that moving the telescope in right ascension precisely mimics the motion of the sky.

The reason for this is that occultations are detected from the parts of the Earth where the shadow of the asteroid passes, the path of the shadow and the duration of the occultation can be predicted (with uncertainties), thus, one only has to go chase the shadow. This can happen in the middle of nowhere, often the predictions are updated and the observer has to install the telescope hoping that it is in the correct place in the correct time because the events can last a few seconds only. Precise time and position are required, the occultation kit includes a Global Positioning System (GPS), and a fast camera, in this case I used a Watec camera. I participate, and went to observe in four stellar occultation of binary asteroids. (Fig. 2.3).

Observatoire de Haute-Provence (OHP) / 1.20 m Telescope

I performed observations at the Observatoire de Haute-Provence (OHP), located in the southeast of France (IAU code: 511). Here I used the 1.20m newtonian telescope, f/6 ( f = 7.232m) equipped with an Andor Ikon L 936 camera which has a CCD 2048×2048 and a Field of view (FoV) = 13.1'×13. 1'. (Fig. 2.4). I used the filter wheel with SDSS filters to collect photometric data for colors and lightcurves of binaries (Ch. 4).

Pic du Midi Observatory / 1 meter Telescope (T1M)

Pic du Midi is a facility in the French Pyrenees (IAU code: 586). I used the 1 meter telescope (T1M), D=1,05m F/D=5. This tool is equipped with a CCD camera with a sensor Marconi DZ936BV with a resolution arcsec/ pixel = 0.21. I used the filter wheel with SDSS filters (Fig. 2.5) to collect photometric data for colors and lightcurves of binary asteroids (Ch. 4).

La Silla Observatory / New Technology Telescope (NTT)

The New Technology Telescope (NTT), has an Alt-Az mounting, and is a 3.58m Richey-Chretien telescope that was the prototype of active optics (AO), its parameters are: f/2.2, D=3.58m. Its primary mirror can be slightly deformed. This Observatory is located at the outskirts of the Atacama Desert in Chile and is a complex of several telescopes, large and small (IAU code: 809, Fig. 2.6). Here I used the ESO Faint Object Spectrograph and Camera 2 (EFOSC2) with the Gunn filters (g r i z) for colors and lightcurves of KBOs and the comet 67P/Churyumov (Ch. 4).

Telescopes

Infra Red Telescope Facility -IRTF

This is NASA telescope at the summit of Mauna Kea, designed for IR observations (IAU code: 568, Fig. 2.7). Its primary mirror has 3m. Here I used the spectrometer Spex to acquire spectra of binaries without taxonomy (Ch. 3). In this case I observed remotely from CODAM, Observatoire de Paris at Meudon.

Large facilities for high angular resolution

I have collected data from several large telescopes, most of them AO images from the archives of the The Canadian Astronomy Data Centre (CADC) http://www.cadc-ccda.hia-iha.nrc-cnrc. gc.ca/ to study the orbit of the satellite of binary asteroid (107) Camilla (Ch. 5).

• Very Large Telescope (VLT)

This ESO telescope is located at Cerro Paranal at the Atacama desert near Antofagasta, Chile (IAU code: 309, Fig. 2.8). The VLT is a complex of 4 identical 8.2-m Unit Telescopes (UT) Ritchey-Chrétien style. The four telescopes can be operated separately or combined in interferometric mode (there are also other 4 auxiliary telescopes) and can detect from UV to mid-IR.

The AO images of Camilla were detected with both the NACO and SPHERE, first and second generation Adaptive Optics instruments respectively. In the case of SPHERE, with the Infra-Red Dual-beam Imager and Spectrograph (IRDIS) camera with the integral Field Spectrometer (IFS) in IRDFIS mode (IRDIS and IFS observing simultaneously).

Telescopes

Sky surveys and Catalogs

In current times there exist a wealth of data that has increased tremendously if compared with the past decade (not to mention the time before). Sometimes data is reserved to the groups involved in the projects, but often it is released after some time. I will explain how one can get data from several servers or databases.

There are several survey catalogs of asteroids based on optical to near-infrared observations: the 2MASS Asteroid Catalog [START_REF] Sykes | The 2MASS Asteroid and Comet Survey[END_REF] compiles near-infrared colors of 1054 asteroids based on the Two Micron All Sky Survey -2MASS; the Subaru Main Belt Asteroid Survey (SMBAS) [START_REF] Yoshida | Subaru Main Belt Asteroid Survey (SMBAS)-Size and color distributions of small main-belt asteroids[END_REF] gives the size and color distributions of 1,838 asteroids observed with the Subaru telescope; the SDSS Moving Object Catalog, described above. Data on solar system objects are often ancillary results from surveys designed primarily to investigate astrophysical sources beyond the Solar System. From different surveys -in general dedicated to distant objects-there has been observed also moving objects like asteroids. Two of the most important surveys gathering these data are:

1. The Sloan Digital Sky Survey Moving Object Catalog SDSS -MOC [START_REF] Ivezić | Solar System Objects Observed in the Sloan Digital Sky Survey Commissioning Data[END_REF][START_REF] Parker | The Size Distributions of Asteroid Families in the SDSS Moving Object Catalog 4[END_REF] provides accurate astrometric and 5-band photometric measurements. Now in its fourth release (MOC4), it has produced the largest available catalog of multi-color photometric measurements for asteroids [START_REF] Ivezić | Color Confirmation of Asteroid Families[END_REF][START_REF] Juric | The SDSS Moving Object Catalog, Asteroid Data Release 4[END_REF] and has done in total ∼450,000 observations (until March 2007) with 100,000 unique and identified asteroids out of 250,000 observations, and 200,000 unidentified objects. I have use data from this release in Chapter 3.

2. The Visible and Infrared Survey Telescope for Astronomy VISTA Hemisphere Survey (VHS) MOVIS catalog. Which so far has identified 39,947 objects from the Data Release 3 (DR3) in near infrared [START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF]. VISTA is equipped with astounding capabilities from state of the art optics, it is already giving us precious information on Solar System objects like asteroids. I had use data from this release in Chapter 4.

Additional resources

Data volume is increasing dramatically in astronomy as detectors and telescopes become more advanced and powerful. Solar System objects data has been collected in sky surveys providing more and more accurate measures and in the coming future this will be increasing more. First and foremost of course the NASA's Astrophysics Data System Abstract Service (ADS) and Data Archive is the place to look for data and information in astronomy.

For this work I have used several online compilations. My sincere gratefulness to the persons who do this work of compiling and putting on line this information. To access catalogs and online resources, the virtual observatory offers convenient tools. During this project I have used extensively Miriade [START_REF] Berthier | Miriade: A Service for Solar Sytem Ojects Ephemerides in the VO Framework[END_REF], which is part of the more general IMCCE-VO Solar System portal in the Virtual Observatory (VO) framework. The IMCCE ephemeris service on the web2 provides positional and physical ephemerides of planets and small bodies of the Solar System, as well as some physical data. Miriade features several functions (SSODNET, SKYBOT, AstroId, etc), of them I have used extensively SKYBOT.

SKYBOT3 is a service developed by [START_REF] Berthier | SkyBoT, a new VO service to identify Solar System objects[END_REF] at IMCCE. The core of SkyBoT is a database of pre-computed ephemeris of all of the known Solar System objects (asteroids, planets, natural satellites and comets) over a period of years that extends from 1889 to 2060. The ephemerides provided by SkyBoT are J2000 astrometric geocentric or topocentric equatorial coordinates (right ascension and declination) at the requested epoch. It also provides position and motion vector at a specified epoch. The right ascension and declination of the targets are computed by numerical integration of the 8 bodies pertubed problem, taking into

Data Reduction

the information regarding the image: how it was obtained, and, in some cases, how it was processed, this is called a header. Headers contain: name of object, date, exposure time, number of bins, filters used, etc.

Adaptive Optics

Before entering the atmosphere, light from a distant source comes as a plane wave. The speed of light varies as the inverse of the refractive index n. Earth atmosphere is not homogeneous, it has different layers that fluctuates. Fluctuations in n are proportional to the fluctuations in the atmospheric temperature. As light passes through the different layers, speed changes and the original plane wave is deformed. This also depends on the wavelength, since the wave vector k is related to it in this form:

|k| = 2π/λ.
Adaptive optics is a technology that corrects in real time for the blurring effects of atmospheric turbulence by means of monitoring the wavefront distortions and compensating for it using different mechanisms like deformable mirrors or tip-tilt correction8 . In this way the wavefront is turned planar again; thus, the image can be obtained at the diffraction limit (Fig. 2.15).

Large ground-based telescopes like Keck, Gemini, VLT, count with AO systems.

Electronic Detectors

Astronomical detectors may be different in nature, for this work I had used Charge Coupled Devices (CCD) detectors for all the observations at visible wavelengths, and Aladdin Arrays for the NIR wavelengths. These detectors have several advantages compared with others like ancient photographic plates. They have also some limitations.

• CCD

A CCD consists of an array of semiconductor capacitor elements called "wells" or pixels. When a photon strikes a pixel, then, with a certain probability, an electron is freed from the semiconductor and stored in the well. In that way, CCDs convert optical images into electronic images (Fig. 2.16). When the exposure is finished, the stored electron charges are transferred from well to well, and finally past an amplifier and a analog-to-digital converter (ADC) that converts the charges into analog data units ("ADUs") which are stored electronically.

Because the efficiency of CCDs is not 100%, not all the pixels which are read out from the CCD chip represent the data we are interested in. Occasionally a cosmic ray strikes a pixel, and leaves some signal that will appear in the raw image.

Among the many advantages that CCDs have, we can mention:

Chapter 2. Data & reduction

Signal to Noise Ratio or S/N

The signal to noise ratio (S/N ) for a point or extended source depends on both the Poisson noise10 of the object, and on noises associated with the background. Sources of background noise include "read noise" of the CCDs, and Poisson noise in the dark current, sky background, and any intrusive light superposed on the target.

The equation for the S/N of a measurement with a CCD is given by the formula [START_REF] Howell | Handbook of CCD Astronomy[END_REF]:

S N = N * N * + n pi x (N S + N D + N 2 R ) (2.3)
where:

N * is the total number of photons (signal) collected from the object of interest.

The "noise" terms in the above equation are the square roots of N * n pi x is the number of pixels under consideration for the S/N calculation, N S is the total number of photons per pixel from the background or sky, N D is the total number of dark current electrons per pixel, N 2 R is the total number of electrons per pixel resulting from the read noise.

Calibration frames

BIAS frames

The amplifier that increases the signal before the ADC, has a built-in offset or bias, which ensures that the ADC always receives a positive signal. This offset must be removed if the data values are to be truly representative of the counts recorded per pixel. Thus, the first step in reducing CCD images is to remove the bias from all digital images. To achieve this we obtain BIAS frames. This is a zero seconds exposure with the shutter closed so that no photons fall on the chip. In theory these frames contain only bias numbers and some readout noise. By subtracting one frame, or the average of several frames, from each subsequent image the bias is removed (Fig. 2.17).

Flat field frames: FLAT

This refers to correcting the CCD throughput at each pixel so that each one would respond equally to a source with the same photon flux. This is necessary because there

Spectroscopic survey of binary asteroids

In nature, the various observed characteristics that objects shows, allow us to group them. This classification is a first step of study which can be very exhaustive if we can find ways to identify the more fundamental properties of objects, like spectra. Spectra of planetary bodies shows differences which gives us information on the surface of the body and with that, of the processes that this body has experienced (heating, aqueous alteration, weathering...). They present different shapes, slopes, some of them absorptions features. Thus, Solar System objects are grouped according to the similarity of their spectra.

This of course has improved as a wider wavelength range has become available, showing processes hidden in the visible part of the spectrum.

In an intuitive way, the tendency has been to establish a relation between the taxonomic classes and mineralogies, comparing asteroid reflectance spectra with those obtained from meteorites and different minerals in the laboratory. The first rigorous asteroid taxonomy was developed by [START_REF] Chapman | Surface properties of asteroids -A synthesis of polarimetry, radiometry, and spectrophotometry[END_REF] based on a synthesis of polarimetry, radiometry, and spectrophotometry for a sample of 110 asteroids, in it, only two classes were formally recognized: C and S, with other unusual spectra labeled U. Similar was the one developed by [START_REF] Bowell | Taxonomy of asteroids[END_REF] in which classes were denominated according to the mineral associated with the spectrum: the C class was associated to carbonaceous chondrites, the S class to stony-iron meteorites, the E class to enstatite achondrites, and the M class to the metallic iron-nickel meteorites. Subsequent taxonomies by [START_REF] Tholen | Asteroid taxonomy from cluster analysis of photometry[END_REF] taxonomy based on results from the Eight-Color Asteroid Survey [ECAS, [START_REF] Zellner | The eight-color asteroid survey -Results for 589 minor planets[END_REF] with 14 recognized classes. This system takes advantage of the wealth of information that can be gathered with CCDs even to obtain information from spectra of small asteroids [START_REF] Barucci | Classification of asteroids using G-mode analysis[END_REF][START_REF] Tedesco | Threeparameter asteroid taxonomy classifications[END_REF], Bus and Binzel, 2002].

Tholen [1984] uses principal components analysis (PCA), which is an attempt to reduce the dimensionality of the problem of classification, of the eight-color data, but this changed little by little as the observations improved in quantity and quality and classification algorithms turned better. Also, differences were recognized in spectra and the number of classes increased as large as 26 in Bus and Binzel [2002], to be later redefined to 24 classes when including Near Infrared reflection spectra in the taxonomy developed by DeMeo et al. [2009] using PCA (Fig. 3.1).

Part of the aims of this work was to assess the taxonomy of binary asteroids with unknown spectral classification to determine their composition for the first time and study how taxonomic class distributes among binaries. The characterization of binaries physical properties from the ground is possible by spectroscopy in both visible and infrared spectral regions.

When possible, mineralogical composition can be established.

On asteroid classification and meteorites

The goal of asteroid classification is to group them according to their compositional -mainly superficial-resemblances obtained from spectroscopic observations, and to identify the samples that arrive on Earth, and whose spectra are obtained in laboratories, as coming from some common origin or asteroid parent bodies (this includes other bodies like planets or the Moon). Nowadays, geologic studies plays an important role in the groupings of meteorites according to petrologic, mineralogical, bulk-chemical, and isotopic properties. This suggest the existence of 100-150 distinct parent bodies. The diverse composition found in meteorites gives clues on the processes that these bodies went through and besides information of their parent body formation processes, they can reveal also collisional processes that can reveal the interior of differentiated bodies which in turn can give insights on the age and mass of the parent body (Fig. 3.2).

On asteroid classification and meteorites

• Asteroid classes There are several classification schemes that appeared since the 1970's, they employs single-letter designations. This began with C, and S types, each letter relates to the -at the time-inferred composition of an asteroid: C (carbonaceous), S (stony), M (metallic), F (flat), R (red), etc. This has changed progressively with a better understanding of these minor bodies. The current standard is Bus-DeMeo taxonomy with 24 classes. A comparison of the evolution of these systems can be seen in Fig. 3.2 taken from Asteroids IV DeMeo et al. [2015]. The most abundant classes or complex are S, C and X.

• Meteorite classifications Meteorites are classified according to their structure and mineralogy, using different analysis: chemical, isotopic, and structural. Three very broad categories are recognized: stones, irons and stony-irons. There are also various subcategories. The most basic separation of meteorites is into unmelted (chondrites) and melted ones (non-chondrites). The chondrites are generally assumed to come from parent bodies that were smaller and/or formed later that those of the non-chondrites, although some chondrites may be the unmelted crusts of differentiated bodies. For further subdividing meteorites, the most useful classification tools reflect the meteorites nebular (primary) and parent body (secondary) characteristics. A significant number of meteorites do not fit into the established groups. The convention is that groups must be composed of five or more members, so these meteorites are classified as ungrouped.

• Types of minerals involved The relevant minerals in asteroids are determined from spectrum analysis and also the retrieval of some samples (with spatial missions). For the S-complex, the minerals involved are olivine and pyroxene. In the C-complex: opaques, carbon, phyllosilicates, and according to their spectrum, they can have also olivine and pyroxene. In the case of the X-complex which includes asteroids with different albedos, the minerals are opaques, carbon, low-Fe pyroxenne, enstatite, oldhamite. In the case of the other classes (end members and outliers) the composition can include pyroxene, olivine and also organics, plagioclase feldspar, pallasite, brachinite, etc. Anhydrous pyroxene-rich from interplanetary dust particles (IDPs) have been proposed also as surface analogs for about two-thirds of all C-complex asteroids. Chapter 3. Spectroscopic survey of binary asteroids

Reflectance Spectra

Reflection spectra provides information about the top-most layers of the surface of asteroids. Mineral compositions of asteroids are inferred from visible and near-infrared reflectance spectroscopy.

Reflectance

λ (object) = Flux λ (object) Flux λ (standard) (3.1)
Here, the standard is a telluric standard star, of which observations are required for all NIR spectroscopic observations to cancel telluric (atmospheric) strong and variable absorption features due to the Earth's atmosphere in the data obtained. This star must be near in both time and sky position (air mass) to the object.

Near infrared Spectra (NIR)

Statistical work on spectral data allows the construction of taxonomic systems, a first step in studies of comparative planetology. The current taxonomy for asteroids by DeMeo et al.

[2009] underlines the importance of both visible and near-infrared spectral data in asteroid classification statistics. This is quite understandable as the characteristic absorption bands for regoliths on asteroid surfaces are located in the 0.4-3.6 µm spectral region1 . Also, with few exceptions, this spectral region is accessible from the ground, the atmosphere being mostly transparent to these wavelengths.

NIR spectra of S type asteroids are dominated by two bands, a broad band at about 1 µm caused by pyroxene and olivine absorptions, and a broad band at about 2 µm caused predominantly by pyroxene. The variations in the compositions of these minerals and the presence of minor minerals such as metal and plagioclase affect the position and width of these two bands (Fig. 3.1).

Why determine binaries taxonomy?

There are about 700,000 known asteroids, most of them belonging to the Main Belt. Among small asteroids (up to 10-15 km), about 15 ± 4% are binary asteroids [START_REF] Margot | Asteroid Systems: Binaries, Triples, and Pairs[END_REF]. We currently know 213 systems. Unfortunately, spectral classification is missing for 127 (60%) of them [START_REF] Johnston | Binary Minor Planets V9.0[END_REF], and the density has been estimated for only 54 systems (25%). It is crucial to gather spectral classifications of these minor bodies, as well as to monitor the relative position of the satellites around them to derive their density [START_REF] Carry | Density of asteroids[END_REF]. This will help us to better constrain the properties of these minor bodies such as internal structure, and Table 3.1 -Observational circumstances for each asteroid. Asteroid designations, mid-date of observation (UT), apparent magnitude (V), phase angle (α), heliocentric distance (∆), airmass (AM), the integration time for each spectrum (IT), and the number of cycles of each observation are presented. The last two columns describe the solar analogs (SA) used for data reduction as well as their airmass at the observing time (AM S A ). Our aim is also to investigate whether small binaries -as is the case of the sample in this workare more frequent among some kind of taxonomic class or not and if this is consistent with a binary formation mechanism that involves YORP-induced spin-up and rotational fission and mass shedding [START_REF] Walsh | Rotational breakup as the origin of small binary asteroids[END_REF][START_REF] Walsh | Formation and Evolution of Binary Asteroids[END_REF][START_REF] Margot | Asteroid Systems: Binaries, Triples, and Pairs[END_REF].

Binaries NIR Spectra Observed with Spex

In this first part of the chapter, I present spectroscopic results for one Mars Crosser and four Main Belt asteroids (Fig. 3.5) in the 0.8-2.5 µm spectral region. These objects were observed during the night of September 29, 2015 granted by the NASA Infrared Telescope Facility (IRTF). In Section 3.6, I describe the observation method and the data reduction process. In section 3.7

I present the methods that we use to model and analyze the data and interprete the obtained spectra to assess the composition and mineralogy of the asteroids. In Section 3.8, I present the current available information on these binaries with the results of the spectral analysis for each body.

Observing method and data reduction

I observe the asteroids and the solar analogs (for telluric corrections and removal of the solar continuum) alternatively during the run. In order to have the least amount of airmass, we scheduled the observations of all asteroids as close to the meridian as possible, preceded by the observation of their solar analogs. The search for these stars was done with the star locator on the IRTF webpage2 . The photometrical G2V standards were chosen, with the following stars used as solar analogs: HD 377, HD 7983, HD 232824, each of them close to their respective asteroid (see details in Table 3.1).

The asteroids were observed in the 0.8 -2.5 µm spectral region with SpeX the low-to mediumresolution near-IR spectrograph and imager [START_REF] Rayner | SpeX: A Medium-Resolution 0.8-5.5 Micron Spectrograph and Imager for the NASA Infrared Telescope Facility[END_REF], on the 3-meter NASA IRTF located on Mauna Kea, Hawaii. Observations were performed remotely from the Centre d'Observation à Distance en Astronomie à Meudon [CODAM, Birlan et al., 2004[START_REF] Birlan | Near infra-red spectroscopy of the asteroid 21 Lutetia. I. New results of long-term campaign[END_REF] using the low resolution Prism mode (R = 100) of the spectrograph. We used a 0.8×15 arcsec slit oriented North-South. The spectra for the asteroids and the solar analog stars were obtained alternatively on two separated locations on the slit denoted A and B using the nod d i ng procedure [START_REF] Nedelcu | Near infra-red spectroscopy of the asteroid 21 Lutetia. II. Rotationally resolved spectroscopy of the surface[END_REF] 3 . We follow the SpeX Observing Manual [START_REF] Rayner | SpeX Observing Manual[END_REF] throughout the run and for the reduction of the data, we used Spextool (SPectral EXtraction TOOL), an Interactive Data Language (IDL)-based data reduction package written by [START_REF] Cushing | Spextool: A Spectral Extraction Package for SpeX, a 0.8-5.5 Micron Cross-Dispersed Spectrograph[END_REF] to reduce data obtained with SpeX.

The circumstances of observations are presented in Table 3.1. All the asteroid spectra were obtained taking images with an integration time (IT) of 120s in the nodding procedure for several cycles, in order to increase the signal to noise ratio (S/N ). For asteroids (2691) Sersic and (8373) Stephengould, the atmospheric conditions and their low brightness imply a poor S/N . The weather conditions of the night were: seeing 0.6 arcsec, humidity (at the beginning of the run) 16%, we note the presence of clouds during the run and temperature of 4.5 • C.

Methods used to analyze data

For the analysis, I gather information of all previously published physical and dynamical properties of the asteroids observed. Table 3.2 summarizes some parameters of the sample, and also the taxonomic classification given in this work. The only visible spectral counterpart available for this analysis was for (8373) Stephengould. For the other cases, were the visible range was lacking, the slope was computed for the spectra normalized to 1.25 µm. I also found Sloan Digital Sky Survey (SDSS) colors for (4383) Suruga, which were included in the analysis.

Methods used to analyze data

For analyzing the spectra, I used M4AST (Modeling for asteroids), a public software tool developed at the IMCCE by [START_REF] Popescu | Modeling of asteroid spectra -M4AST[END_REF] and proposed as a centralized database for all published data that currently contains more than 7,000 spectra of asteroids, including SMASS MIT's database [START_REF] Binzel | Observed spectral properties of near-Earth objects: results for population distribution, source regions, and space weathering processes[END_REF] and libraries such as RELAB [START_REF] Pieters | Strength of mineral absorption features in the transmitted component of nearinfrared reflected light -First results from RELAB[END_REF]. M4AST also proposes methods and routines to achieve taxonomy classification, spectral comparison using [START_REF] Cloutis | Calibrations of phase abundance, composition, and particle size distribution for olivine-orthopyroxene mixtures from reflectance spectra[END_REF] model to compute spectral parameters, and space weathering effects model proposed by [START_REF] Brunetto | Modeling asteroid surfaces from observations and irradiation experiments: The case of 832 Karin[END_REF] in order to model spectra and extract several mineralogical parameters [START_REF] Birlan | M4AST -A Tool for Asteroid Modelling[END_REF]. M4AST is free and available via a web interface. 4Variables like the grain size, packing state, or the viewing geometry are mostly ignored, though these variables can affect the spectral slope and bands [START_REF] Perna | Grasping the Nature of Potentially Hazardous Asteroids[END_REF].

All NIR spectra are normalized to 1.25 µm and are plotted in Fig. 3.5 with error bars. In the case of ( 8373 The discussion about taxonomic type of each object is made with reference to Fig. 3.5. The results for taxonomic classification of spectra are synthesized in Table 3.2 to allow a comparison with the physical properties. Table 3.4 summarizes the comparison of asteroid spectra with those of meteorites from RELAB spectral database 5 . The corresponding figures are in Appendix A.1. taxonomical system, and we report the best three matches, with their χ 2 . For (4383) Suruga spectrum, five points from SDSS photometry were converted to reflectance [using the transformation by [START_REF] Bilir | Absolute magnitudes for late-type dwarf stars for Sloan photometry[END_REF][START_REF] Rodgers | Improved u'g'r'i'z' to UBVR C I C Transformation Equations for Main-Sequence Stars[END_REF] and added. Shaded in light grey are wavelength ranges affected by atmospheric absorption [START_REF] Lord | A new software tool for computing Earth's atmospheric transmission of near-and far-infrared radiation[END_REF]. All spectra are normalized to unity at 1.25 µm. Light blue corresponds to the best match spectra from RELAB library for each asteroid.

Results on individual targets

Results on individual targets

(2691) Sersic

This asteroid was discovered on May 18, 1974 from Felix Aguilar Observatory, El Leoncito, Argentina. Its companion was revealed from photometric observations by Oey et al. [2011] on June 2011. With an absolute magnitude of H = 13.4, and a geometric albedo of p v = 0.261 ± 0.062 [START_REF] Masiero | Main Belt Asteroids with WISE/NEO-WISE. I. Preliminary Albedos and Diameters[END_REF], this object has an estimated diameter of 5 ± 0.11 km [from the effective diameter of the system, its albedo, and the combined H , [START_REF] Johnston | Binary Minor Planets V7.0[END_REF].

Sersic is an inner main belt asteroid, next to the Flora family, near the ν 6 secular resonance, a source region of near-Earth asteroids [START_REF] Binzel | Observed spectral properties of near-Earth objects: results for population distribution, source regions, and space weathering processes[END_REF]. Average properties of this family are: taxonomic class S [mainly obtained from visible spectroscopy, [START_REF] Florczak | A Visible Spectroscopic Survey of the Flora Clan[END_REF]] and p v = 0.305 ± 0.064 [START_REF] Masiero | Asteroid Family Physical Properties[END_REF].

From spectroscopic observations of Flora members combined with analyses of meteorite samples, [START_REF] Vernazza | Compositional differences between meteorites and near-Earth asteroids[END_REF], de [START_REF] De León | Observations, compositional, and physical characterization of near-Earth and Mars-crosser asteroids from a spectroscopic survey[END_REF], and [START_REF] Dunn | Mineralogies and source regions of near-Earth asteroids[END_REF] had linked LL chondrite meteorites to the Flora family. No spectrum has been published for (2691) Sersic previously.

With M4AST online tool, using χ 2 method with Bus-DeMeo taxonomy [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] system, this asteroid was classified as Sr-type [with a reliability factor6 of 78.0%, [START_REF] Popescu | Modeling of asteroid spectra -M4AST[END_REF] with a close fit with S and O type using standard error and mean square methods respectively. The spectrum shows a shallow absorption feature around 1µm. Owing to the paucity of known O-type asteroids, and the fact that S-types dominate the inner main belt population [DeMeo and Carry, 2013Carry, , 2014]], the probability is higher for it to be an S-type classification for Sersic, over a less-likely O-type (Fig. 3.5).

Comparison with Relab database from the M4AST tool, shows that using χ 2 method, the best spectral fit is obtained with Los Angeles meteorite (stone 1) (Sample ID:MT-JLB-006-C, This corresponds to a Shergottite, a martian meteorite (basaltic to lherzolitic igneous rocks) with chip natural texture. This doesn't match well with this asteroid, since Shergotittes have estimated time of formation of 1×10 6 years [START_REF] Jagoutz | SR and Nd isotopic systematics of Shergotty meteorite[END_REF] while the Flora family lifetime is 1×10 9 years [START_REF] Nesvorný | The Flora Family: A Case of the Dynamically Dispersed Collisional Swarm?[END_REF]. For this reason we are considering the other closer analogues. The second match is for meteorite Hamlet (Sample ID OC-TXH-002-A20), an LL4 ordinary chondrite; the third match is for another sample of Los Angeles meteorite (Sample ID MT-JFM-005) again a Shergottite. The fourth, fifth and sixth matches are all Ordinary Chondrites, meteorites: Soko-Banja (OC/LL4, Sample ID MR-MJG-070), Barratta (OC/L4, Sample ID MH-CMP-002), and Bjurbole unshaken (OC/L4, Sample ID MP-FPF-027).

The poor S/N makes the analysis very hard to do. Only the NIR part of the spectrum is available, therefore we can compute only the band minima. The first minimum is at 0.9161 ± Chapter 3. Spectroscopic survey of binary asteroids 0.0054µm (Fig. A.5). The spectrum exhibits spectral variations around 1.45 µm and 1.9 µm due to the influence of telluric water that remained even after the data reduction.

Being (2691) Sersic an Sr-type asteroid, no attempt to model space weathering was conducted due to the low S/N . Better S/N NIR spectra are thus needed, together with visible counterpart, to understand the reflectance properties of Sersic.

(4383) Suruga

Suruga, a Vestoid [i.e., a fragment of asteroid ( 4) Vesta, [START_REF] Binzel | Chips off of asteroid 4 Vesta -Evidence for the parent body of basaltic achondrite meteorites[END_REF], was discovered in December 1989 from Gekko, Japan by Y. Oshima. Its companion was detected on February 2013 using lightcurve observations. The rotation period of the primary is 3.4068 ± 0.0003 h with an amplitude of 0.14 ± 0.01 mag, indicating a nearly spheroidal shape. The orbital period of the satellite is 16.386 ± 0.001 h [START_REF] Warner | Something Old, Something New: Three Binary Discoveries from the Palmer Divide Observatory[END_REF]. The ratio D s/D p ≥ 0.21± 0.027 . This object has a geometric albedo p v = 0.320 ± 0.038 [START_REF] Masiero | Main Belt Asteroids with WISE/NEO-WISE. I. Preliminary Albedos and Diameters[END_REF]. The diameter of the primary is 6.33 ± 0.09 km and has been derived from lightcurves [START_REF] Johnston | Binary Minor Planets V7.0[END_REF]. A NIR spectrum has been published by de Sanctis et al. [2011]. We will compare the present results with theirs data. This is the only asteroid from the sample that had a previous taxonomy, it was identified as V-type; the M4AST online tool for taxonomy also classified this object as belonging to V-class (Fig 3.5).

This spectrum shows two prominent absorption features at 1 and 2 µm, typical of V-class asteroids. When comparing with spectra from Relab database, we found spectral matches with the achondrite meteorite Pavlovka, a howardite achondrite (Sample ID:MR-MJG-094). These type of meteorites are thought to have originated from the crust of the asteroid Vesta (Table 3. 4,Fig. A.2). Other spectra that fits Suruga NIR spectrum corresponds to samples of particulates (0-25 µm) of the meteorites Le Teilleul (Sample ID:MP-TXH-093-A), Frankfort howardite (Sample ID:MP-TXH-085-A), and "Y-7308,142" (Sample ID:MP-TXH-097-A) all of them Howardite-Eucrite-Diogenite (HED). This matches suggests that the asteroid might be covered by a fine regolith layer. Two other matches corresponds to meteorites Kapoeta P11410 (Sample ID: SN-CMP-012) an achondrite HED Breccia and "GRO95574,9" (Sample ID: MP-TXH-125) a basaltic HED regolith breccia. This spectrum was acquired with a high S/N which ensures a small error in computing the position and depth of the band minima. The first minimum is at 0.9254±0.0007 µm and the second minimum is at 1.9710±0.0042 µm which implies a band separation of 1.0456 µm (Fig. A.6). It can also be seen a weak ∼1.2 µm feature. For basaltic achondrites this is indicative of the presence of feldspar. The feature is weak in the spectra of howardites [START_REF] Hardersen | Mineralogy of Asteroid 1459 Magnya and implications for its origin[END_REF]. The normalization of this spectrum was made for the wavelength: 1.250 µm.

Because, only the NIR part of the spectrum is available, and as such solely the band minima can be computed, we look at data in SDSS catalog [START_REF] Ivezić | SDSS Moving Object Catalog V3.0[END_REF] and found the magnitudes in ug r i z filters. We converted them into spectral reflectance [START_REF] Zellner | The eight-color asteroid survey -Results for 589 minor planets[END_REF]: log R λ = ±0.4c λ (where c λ is the tabulated color index and the negative sign is chosen for wavelengths shorter than visual) and the transformations for the colors of the Sun into reflectance using the Bilir, Karaali, and Tuncel transformation for g filter [START_REF] Bilir | Absolute magnitudes for late-type dwarf stars for Sloan photometry[END_REF][START_REF] Rodgers | Improved u'g'r'i'z' to UBVR C I C Transformation Equations for Main-Sequence Stars[END_REF]. With these new "reflectance points" we complete the visual part of the spectrum we got (Fig. 3.5), and compute the Band Area Ratio BAR=2.6±0.4 and then compute the mafic mineral composition according to [START_REF] Gaffey | Mineralogy of Asteroids. Asteroids III[END_REF] (Fig. 3.6). We found W O 7 and F S 45 and the mineral abundances in the olivine-orthopyroxene mixture Ppx/(Opx)+ Ol = 1.1±0.2. We note, however, that although the band I area is uncertain owing to the poor sampling of the visible part, the BAR we derive is consistent with those of V-type asteroids [START_REF] Moskovitz | A spectroscopic comparison of HED meteorites and V-type asteroids in the inner Main Belt[END_REF].

Using M4Ast analysis with de Sanctis et al. [2011] spectrum of Suruga: the first minimum is at 0.9023±0.0018 µm and the second minimum is at 1.8770±0.0072 µm which implies a band separation of 0.9747 µm (Fig. A.6). Comparing with the present work values, there is a notorious difference with the second minima value. This is understandable because De Sanctis spectrum values under M4Ast scheme are slightly noisy around 1.9µm. In the original work by de Sanctis et al. [2011], BII minimum is 1.91±0.005µm. In conclusion, this is a V-type asteroid.

Chapter 3. Spectroscopic survey of binary asteroids

(7187) Isobe

Asteroid (7187) Isobe was discovered by E. F. Helin in January 30, 1992 from Palomar Observatory, California, USA. It orbits in the Hungaria region8 , owing to its small size it might have been drifted by Yarkovsky effect and get trapped by secular resonances [START_REF] Mceachern | Dynamical evolution of the Hungaria asteroids[END_REF]. Isobe has been studied by extensive lightcurve observations since 2004 [Warner, 2005[START_REF] Warner | Asteroid Lightcurve Analysis at the Palmer Divide Observatory: September-December 2007[END_REF][START_REF] Warner | Asteroid Lightcurve Analysis at the Palmer Divide Observatory: 2010 December-2011 March[END_REF][START_REF] Warner | Rounding Up the Unusual Suspects[END_REF]. Warner also discovered its companion in August 26, 2012, using ligthcurve observations from Palmer Divide Observatory (PDO) under the PDO observing program, which concentrates on Hungaria asteroids. More recently, lightcurves published by [START_REF] Stephens | Asteroids Observed from CS3: 2015 July -September[END_REF] do not make any evidence of mutual event into the binary system of Isobe.

The period of the primary is 4.2427±0.0002h [START_REF] Warner | Rounding Up the Unusual Suspects[END_REF], while for the secondary, Warner found two possible solutions from which the longer one of 33.22±0.04 h, seems more probable since the "events" are about equally spaced in the overall curve, which may indicate that the satellite is on a circular orbit. In that case, the system is old enough to have evolved by tides because torques from mutual body tides dissipate energy circularize the orbit and affect the rotation rates [Jacobson andScheeres, 2011, Murray and[START_REF] Murray | Solar system dynamics[END_REF].

This asteroid has a magnitude H =13.89, a diameter 6.05±1.46 km, and a geometrical albedo p v =0.134±0.104 [START_REF] Masiero | Preliminary Analysis of WISE/NEOWISE 3-Band Cryogenic and Post-cryogenic Observations of Main Belt Asteroids[END_REF].

No spectrum has been published previously for (7187) Isobe. With M4AST Classification tool using χ 2 approach we find that (7187) Isobe fits a K-type asteroid with a clear absorption band around 1 µm (Fig. 3.5). The reliability of the classification is 80.4%. The local minimum around 1µm was found at 1.0707 µm adjusting a second degree polynomial with R 2 = 0.8532. The fits with Xk and Cg types do not show very well this 1µm feature (Fig. 3.5).

The Relab meteorite sample that best fits is a Particulate Ground Dry-Sieved, Almahata Sitta #4 <125µm meteorite (sample ID: MT-PMJ-093-C), an Achondrite Ureilite Anomalous Polymict (0-125 µm)). Another fit is with a sample of Allende: HC-10 dark inclusion meteorite, a carbonaceous chondrite (sample ID: MT-TJM-073). Allende meteorite is olivine-rich, and contain an abundant matrix that is relatively featureless in the near infrared which explains why the 1µm absorption feature is subtler than in ordinary chondrite spectra [START_REF] Vernazza | Asteroid (21) Lutetia as a remnant of Earth's precursor planetesimals[END_REF]. Meteorite Tsarev (sample ID: MA-ATB-053 OC) an ordinary chondrite, also fits this spectrum. Other meteorite spectra found with M4AST were "LEW87009,16" (sample ID: LM-LAM-011), "EET90021,10" (sample ID: MP-TXH-043), and "LEW87148,15" (sample ID: MP-TXH-016); all of them carbonaceous chondrite. Of the last four spectra the one of "LEW87009,16" fits better the absorption around 1µm.

With the error bar of (7187) Isobe geometrical albedo, it is hard to favor one solution if CC, OC and ureilite are together. However, there is a clear dichotomy between ureilitic and chondritic materials. (Table 3.4,Fig. A.3). Regarding ureilites, this is consistent with the weak mafic iron silicate absorption bands that this spectrum presents in the 1µm and 2µm region according

Results on individual targets

to [START_REF] Cloutis | Spectral reflectance properties of ureilites[END_REF]. The visible counterpart of the spectrum is needed to complete the analysis. With [START_REF] Nimura | An Attempt of Restricting Olivine Bands in the Modified Gaussian Model[END_REF] method we can try to put constraint in the olivine band around 1µm in the Modified Gaussian Model.

(8373) Stephengould

Stephengould was discovered the 1 st of January 1992 from Palomar Observatory, California, USA by C. S. Shoemaker and E. M. Shoemaker. Its companion was discovered in January 2010 by Krugly et al. [2010] using lightcurve observations (reexamination of previous observations shows what appears to be an event overlooked in the original analysis by [START_REF] Warner | Lightcurve analysis for numbered asteroids 301[END_REF]).

Stephengould is a Mars Crosser with an absolute magnitude H =13.8. From the lightcurves, the orbital period of the secondary is 34.15 ± 0.1 hr and the primary rotation period is 4.435 ± 0.001 hr. From mutual events, Krugly et al. [2010] obtained a lower limit on the secondary-to-primary mean-diameter ratio of 0.27. This spectrum is featureless (Fig. 3.5), although it shows some artifacts. The bad S/N does not permit to draw more conclusions. A composite VNIR spectrum by de León et al. [2010] was found in the literature and the NIR spectrum in this work has similar trends with it. Into our analysis we used the visible spectrum of de [START_REF] De León | Observations, compositional, and physical characterization of near-Earth and Mars-crosser asteroids from a spectroscopic survey[END_REF], merge it with our NIR data, and compare the results of these two composite spectra. The composite spectral slope is 0.262 with a correlation of 0.8 which is in agreement with the one of de [START_REF] De León | Observations, compositional, and physical characterization of near-Earth and Mars-crosser asteroids from a spectroscopic survey[END_REF], we can observe a similar positive slope in the spectrum (Fig. A.8).

With M4AST classification tool using χ 2 approach based on Bus-DeMeo taxonomy [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] we find that the taxonomic type that best fit this spectrum is X-type followed by T and D type with a reliability of 75.6%. The normalization of this spectrum was made for the wavelength: 1.250 µm (Fig. 3.5).

Comparison of the asteroid spectrum with Relab samples, the best fits of the spectra were for the mesosiderite Veramin (Sample ID: MR-MJG-084), rock meteorite "Finest Octahedrite, Plessitic(0.15mm) IRANOM" Butler (Sample ID: MR-MJG-081), ordinary chondrite Pervomaisky (Sample ID: RS-CMP-064), carbonaceous chondrite Tagish Lake ET01-B (Sample ID: MT-MEZ-011), rock Medium Octahedrite IIIAB Chulafinnee (Sample ID: MR-MJG-082), and sulfide Mundrabilla troilite (Sample ID: MB-CMP-006-P2) (Fig. A.4). D-type asteroids are characterized by low albedos [START_REF] Fulchignoni | The Extension of the G-Mode Asteroid Taxonomy[END_REF], and are scarce in the inner Solar System [see DeMeo et al., 2014, Carry et al., 2016]. T-type asteroids seems to be also not so representative for the entire asteroidal population [DeMeo and Carry, 2014] and could be interpreted as an end-member class. Having no albedo information for Stephengould, and due to the more abundant X type asteroids [DeMeo and Carry, 2013]; this asteroid is more akin to the X-complex, although fits better to D-type (Fig. 3.5). [START_REF] Warner | Lightcurve Analysis of Two Binary Asteroids: (76818) 2000 RG79 and (185851) 2000 DP107[END_REF]). Additional observations in 2008 and 2013 [START_REF] Warner | Lightcurves from the Initial Discovery of Four Hungaria Binary Asteroids[END_REF][START_REF] Pravec | Binary asteroid population. 2. Anisotropic distribution of orbit poles of small, inner main-belt binaries[END_REF][START_REF] Warner | Binary Asteroid Lightcurve Analysis at the CS3-Palmer Divide Station: 2013 June-September[END_REF]] helped refine the system parameters.

Chapter 3. Spectroscopic survey of binary asteroids

This is an Hungaria asteroid (a = 1.929 AU) with an absolute magnitude H =13.7, it has an estimated geometric albedo p v = 0.43. From the lightcurves, the primary rotation period is 3.1669 ± 0.0002 h and the orbital period of the secondary is 14.134 ± 0.002 h [START_REF] Warner | Binary Asteroid Lightcurve Analysis at the CS3-Palmer Divide Station: 2013 June-September[END_REF].

From mutual events, the ratio D s/D p is 0.32± 0.02 according to [START_REF] Warner | Binary Asteroid Lightcurve Analysis at the CS3-Palmer Divide Station: 2013 June-September[END_REF] and D s/D p ≥ 0.35 according to [START_REF] Pravec | Binary asteroid population. 2. Anisotropic distribution of orbit poles of small, inner main-belt binaries[END_REF]. The estimated diameter of the primary is 3.6 km [START_REF] Pravec | Photometric survey of binary near-Earth asteroids[END_REF].

No spectrum has been published previously for (76818) 2000 RG79. The NIR spectrum obtained with Spex (Fig 3 .5) has no features, only a very slight absorption at 2µm and a shallow slope that turns slightly negative around 2.37µm until the end of the spectrum at longer wavelengths. With M4AST Classification tool using χ 2 approach based on Bus-DeMeo taxonomy [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] we find that the taxonomic types that best fit this spectrum are Xc, Xe and Ch types (Fig. 3.5). The reliability of the classification is 82.9%. From inspection of these classification, and comparing with Bus DeMeo MITs classification tool, the match that resembles best the spectrum of the asteroid is Xe type, which are numerous among hungarian [DeMeo and Carry, 2014].

When comparing the asteroid spectrum with Relab samples, the best fits of the spectra were for enstatite chondrite "ALHA81021,89 (EL6) <25um" (Sample ID: MT-PFV-119-B), Achondrite Mayo Belwa (Sample ID:TB-TJM-046), enstatite chondrite "QUE93372,13 (EH5) <25um" (Sample ID:MT-PFV-129-B), enstatite chondrite "ALH84206,25 (EH3) <45um" (Sample ID:MT-PFV-118-A) and enstatite chondrite "KLE98300,33 (EH3) <45um" (Sample ID:MT-PFV-122-A).

The estimated geometric albedo of the featureless spectra of (76818) 2000 RG79 is compatible with enstatite chondrite meteorites [START_REF] Vernazza | Plausible parent bodies for enstatite chondrites and mesosiderites: Implications for Lutetia's fly-by[END_REF].

Results on individual targets

Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance

The previous binary asteroids were observed after the submission and approbation of a proposal sent to IRTF. The second time my proposal was accepted, I was granted the double amount of time. Unfortunately, on the date of the observation a snow storm happened in Hawaii and we could not observe. This is something that happens but of course, research has to continue, I needed more targets to analyze. With that in mind, I looked for data from the MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance collaboration.There, I found several spectra of binaries that were in my observing list. Obviously, these binaries were small, mostly NEAs, some of them were being observed as potential threats to Earth civilization, others, as potential targets to be investigated by space missions; being small and close to the Earth, some of them were tracked in order to detect BYORP effect. These objects are included in this work and as before, with the previous 5 binaries, spectra was classified using M4Ast tool, and I search for matching corresponding meteorite spectra in RELAB. Below I present the results, and in Table 3.5 is the synthesis of all the binaries characterized.

Although taxonomic classification had been performed previously for some of them, I classify all these spectra again with the same protocol as described above in the previous Section 3.8 for consistency.

(88710) 2001 SL 9

Asteroid (88710) 2001 SL9 was discovered in September 18, 2001 from Palomar Observatory, California, USA by Near Earth Asteroid Tracking (NEAT) [START_REF] Helin | Near-Earth Asteroid Tracking (NEAT) Program[END_REF], the autonomous celestial observatory developed by the Jet Propulsion Laboratory/NASA9 . This is an Apollo type near-Earth asteroid. Its companion was discovered in October 2, 2001 by [START_REF] Pravec | SL_9[END_REF] from Ondrejov observatory and Palmer Divide Observatory.

The rotation period of the primary is 2.4004±0.0002 h and the orbital period of the secondary is 16.40 ± 0.02 h [START_REF] Pravec | Photometric survey of binary near-Earth asteroids[END_REF]. This asteroid has a magnitude H =17.6 (JPL). [START_REF] Pravec | Photometric survey of binary near-Earth asteroids[END_REF] get an estimate for the diameter of the primary of 0.8 km (uncertain to a factor of two) and D s/D p = 0.28±0.02. [START_REF] Warner | Near-Earth Asteroid Lightcurve Analysis at CS3-Palmer Divide Station: 2013 September-December[END_REF] observed also this binary in September 2013.

The NIR spectrum obtained with SpeX (Fig. 3.5) shows the typical S-type curve. We find that the taxonomic types that better fits this spectrum are Sr, S, and Sq types with a reliability in the classification of 80.4%. From inspection, the match that resembles best the spectrum is Sr-type.

This asteroid was classified by [START_REF] Lazzarin | Visible and near-infrared spectroscopic investigation of near-Earth objects at ESO: first results[END_REF][START_REF] Lazzarin | Spectroscopic investigation of near-Earth objects at Telescopio Nazionale Galileo[END_REF] as Sr and Q types, they also determined an analog meteorite with VNIR data from Spectroscopic Investigation of Near Earth 3.9. Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance

Objects SINEO [START_REF] Lazzarin | SINEO: Spectroscopic Investigation of Near Earth Objects[END_REF] 10 . de [START_REF] De León | Observations, compositional, and physical characterization of near-Earth and Mars-crosser asteroids from a spectroscopic survey[END_REF] classify it as Q-type. [START_REF] Lazzarin | SINEO: Spectroscopic Investigation of Near Earth Objects[END_REF]] NIR data has low S/N , for this work we had use their visible spectrum (available in MAst libraries) and join it with the NIR spectrum to perform the analysis.

(162483) 2000 PJ 5

This Aten asteroid was discovered on August 4, 2000, by the Lincoln Near-Earth Asteroid Research (LINEAR) program at Socorro, New Mexico [START_REF] Stokes | Lincoln Near-Earth Asteroid Program (LINEAR)[END_REF]. Its binary behaviour was noticed due to their asynchronous rotation from photometric observations obtained by [START_REF] Polishook | Photometry of Aten asteroids-More than a handful of binaries[END_REF] in July, 2005 from Wise Observatory. [START_REF] Polishook | Photometry of Aten asteroids-More than a handful of binaries[END_REF] obtained all the characteristics of this Aten, they even estimate its taxonomy from phase curve parameters, using the correlation between phase and albedo found by [START_REF] Belskaya | Opposition Effect of Asteroids[END_REF]. This Aten has an absolute magnitude H =18.41± 0.05, a geometric albedo p v = 0.2 ± 0.05. Primary rotation period is 2.642 ± 0.001 h and the orbital period of the secondary is 14.16 ± 0.04 h. The estimated diameter of the primary is 0.6 ± 0.1 km and the ratio D s/D p is 0.5.

Even though the NIR SMASS spectrum (Fig 3.9) is a bit noisy, the curves clearly shows absorption features at 1 and 2 µm. With M4AST classification tool using χ 2 approach based on Bus-DeMeo taxonomy [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] we find that the taxonomic types that best fit this spectrum are Q, K and S. (Fig. 3.9). The reliability of the classification is 82.9%. From inspection of these classification, the match that resembles best the spectrum of (162483) 2000 PJ5 is a Q type.

The first minimum is at 0.9591±0.0034 µm and the second minimum is at 1.9669±0.1805 µm which implies a band separation of 1.0078 µm. [START_REF] Gaffey | Mineralogical variations within the S-type asteroid class[END_REF].

Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance

When comparing the asteroid spectrum with RELAB samples, the best fits of the spectra were for the ordinary chondrites: Quenggouk (Sample ID: MR-MJG-042), Bandong (Sample ID: TB-TJM-067), Jelica (Sample ID: MR-MJG-072), Leedey (Sample ID: MR-MJG-060) and the silicate A-881757 (Sample ID: MB-CMP-029-M2).

(190208) 2006 AQ

This asteroid was discovered on 2006 January 2, from Mauna Kea Observatory, Hawaii, USA by D. J. Tholen. Its satellite was discovered by [START_REF] Warner | Two New Binaries and Continuing Observations of Hungaria Group Asteroids[END_REF] on 2014-2015 using lightcurve observations. This NEA type Amor is a so-called wide binary, an unusual binary type (fully asynchronous system, [START_REF] Warner | A Sextet of Main-belt Binary Asteroid Candidates[END_REF]). In these kind of binaries the primary has a long period, ∼hundreds of hours, and the satellite has a short period, with a low amplitude lightcurve; both are well separated, thus the orbital period is long and chances to see mutual events are low. this makes difficult its characterization, only some of the system parameters have been estimated so far. The rotation period of the primary is 182±2 h This asteroid has a magnitude

(348400) 2005 JF 21

This asteroid was discovered on May 4, 2005 from Kitt Peak Observatory, Arizona, USA by Spacewatch Program. Its satellite was discovered by [START_REF] Naidu | [END_REF] with Goldstone radar (8560 MHz, 3.5 cm) delay-Doppler images and echo power spectra, obtained on August 10, 2015. From the images with range resolutions of 150 m, the range extent of the primary is 0.3 km. They found that the two components were separated ∼ 5.4 km in range with no obvious change in the separation during ∼2 hours. They also found a persistent second narrow spike in the echo power spectra consistent with the presence of another satellite that still needs confirmation.

With an absolute magnitude of H = 17.1, and a derived geometric albedo of p v = 0.59, this object has an estimated diameter of 0.6km [from the effective diameter of the system, its

Chapter 3. Spectroscopic survey of binary asteroids albedo, and the combined H , [START_REF] Johnston | Binary Minor Planets V7.0[END_REF]. This NEA is an Amor type and due to its orbital characteristics, it's a Potentially hazardous asteroid (PHA).

The NIR spectrum obtained from SMASS (Fig 3.9) shows two prominent absorption features at 1 and 2 µm, typical of V-class asteroids. Evidently, using M4AST Classification tool with χ 2 approach based on Bus-DeMeo taxonomy [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] the best match is for V type followed by Sv and Sr types (Fig. 3.5). The reliability of the classification is 82.9%. When computing band minima, the first minimum is at 0.9332±0.0008 µm, and the second minimum at 1.9117±0.031 µm which implies a band separation of 0.9785 µm. Only the NIR part of the spectrum is available, and as such solely the band minima can be computed.

Comparing the asteroid NIR spectrum with RELAB meteorite database, all the best matches are Achondrites of varied subtypes: meteorite Kapoeta (ID: MP-TXH-053) subtype Basaltic HED Howardite; mateorite "MIL07001 <45 um" (ID: MT-AWB-168-A) subtype Basaltic HED Diogenite Harzburgitic and meteorite "GRA98108,26 chip" (ID: RM-REM-125) subtype Basaltic HED Olivine-Diogenite are the three best matches.

(374851) 2006 VV 2

This Apollo asteroid was discovered on November 11, 2006 [START_REF] Warner | Lightcurve Photometry Opportunities April-June 2007[END_REF] and the asteroid was surveilled by several astronomers [START_REF] Benishek | CCD Photometry of Seven Asteroids at the Belgrade Astronomical Observatory[END_REF][START_REF] Vereshchagina | Some specific features of light curves of (39) Laetitia, (87) Sylvia, (90) Antiopa, and 2006 VV2 asteroids[END_REF][START_REF] Hergenrother | Photometric Observations of Five Near-Earth Asteroids: (31221)[END_REF][START_REF] Huziak | Ramblings of a Variable-Star Addict: Precise Measurements for Earth-Crossing Asteroid 2006 VV2[END_REF][START_REF] Betzler | Observations of V-type Binary Near-Earth Asteroids 2006 VV2 and 2008 BT18[END_REF][START_REF] Klotz | Courbes de rotation d'astéroïdes et de comètes[END_REF][START_REF] Oey | Lightcurve Analysis of Asteroids from Kingsgrove and Other Collaborating Observatories in the First Half of 2007[END_REF] from different parts of the world. Benner et al. [2007a] report a modestly irregular and asymmetric asteroid with a surface with several prominent concavities, possibly including craters, and features along the leading edges that resemble the pronounced ridge seen along the equator of binary asteroid (66391) 1999 KW4.

The diameter of the primary is 1.06 ± 0.05 km [START_REF] Betzler | Observations of V-type Binary Near-Earth Asteroids 2006 VV2 and 2008 BT18[END_REF]] and > 0.3 km for the secondary [START_REF] Benner | [END_REF]. The maximum orbital distance between the components is at least 1.5 km [START_REF] Benner | [END_REF]. The rotation period of the primary is 2.41 ± 0.005 h [START_REF] Benishek | CCD Photometry of Seven Asteroids at the Belgrade Astronomical Observatory[END_REF], and the orbital period of the secondary is estimated in 0.23 d. It has a magnitude H = 16.6 ± 0.2 [START_REF] Betzler | Observations of V-type Binary Near-Earth Asteroids 2006 VV2 and 2008 BT18[END_REF] and its geometrical albedo is estimated

p v = 0.1.

Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance

For this asteroid, color indices were measured by [START_REF] Betzler | Observations of V-type Binary Near-Earth Asteroids 2006 VV2 and 2008 BT18[END_REF], [START_REF] Hergenrother | Photometric Observations of Five Near-Earth Asteroids: (31221)[END_REF], and [START_REF] Vereshchagina | Some specific features of light curves of (39) Laetitia, (87) Sylvia, (90) Antiopa, and 2006 VV2 asteroids[END_REF], who reported a strong dependence of the shape of the lightcurve on the color.

This spectrum is from [START_REF] Reddy | Mineralogical Survey of near-Earth asteroid population Implications. for impact hazard assessment and sustainability of life on Earth[END_REF] (Fig 3.9). Although no taxonomy has been published (in peer reviewed journals), several taxonomies had been proposed before: from Spex data, V [START_REF] Howell | Thermal Infrared Observations of Several Near-Earth Asteroids[END_REF]; from color indices: S type [START_REF] Hergenrother | Photometric Observations of Five Near-Earth Asteroids: (31221)[END_REF], A type [START_REF] Vereshchagina | Some specific features of light curves of (39) Laetitia, (87) Sylvia, (90) Antiopa, and 2006 VV2 asteroids[END_REF][START_REF] Vereshchagina | Investigation of multiple asteroids 2006 VV2[END_REF], and V, Q or T type [START_REF] Betzler | Observations of V-type Binary Near-Earth Asteroids 2006 VV2 and 2008 BT18[END_REF].

The best matches are for L, Xe and Ch types with a reliability of 90%. However, this spectrum has good S/N and clearly shows absorption features around 1 and 2 µm that are shallow for the proposed taxonomies around 1 µm, and inexistent around 2 µm. MAST has a feature that allows comparison of the spectrum with different types from Bus-DeMeo taxonomy, using it and after visual inspection looking for good fit of the band positions and shapes, we found that the best matches are for Sr and S type (the best matches do not necessarily correspond to the lowest χ 2 values).

When computing band parameters, the first minimum is at 0.9201 ± 0.0013 µm, and the second minimum at 1.9498 ± 0.0037 µm which implies a band separation of 1.0297 µm. Only this NIR spectrum is available, thus, solely the band minima can be computed for ( 374851 [START_REF] Vander Haagen | Lightcurve of Binary Minor Planet 2005 NB7[END_REF]. The diameter of the primary is 0.5 ± 0.1 km [Shepard et al., 2008] and the ratio D s/D p is > 0.32 [Kusnirak et al., 2008]. [START_REF] Somers | Optical Characterization of Planetary Radar Targets[END_REF] already reported this asteroid as Sq in Bus Taxonomy and [START_REF] Gietzen | IRTF observations of S complex and other asteroids: Implications for surface compositions, the presence of clinopyroxenes, and their relationship to meteorites[END_REF] had already studied a Spex NIR spectrum and classify it as an Sq type in Bus DeMeo scheme.

The NIR spectrum shows clearly an absorption around 0.9 µm and a slightly shallow absorption around 2µm. The best match is for Sq type followed by S and Q types (Fig. 3.5). The reliability of the classification is 82.9%. However, the band parameters could not be computed with the tool, by means of a polynomial adjustment we estimate 0.95 µm for the first minimum.

Comparing the asteroid NIR spectrum with RELAB meteorite database, the best matches are for different type of meteorites: OC/L6 Chateau Renard (L6) <125 µm pellet irradiated with 5 mJ + 10 mJ + 20 mJ laser (ID: OC-TXH-011-D35), Igneous/Shergottite EETA79001,73 (ID: LM-LAM-007-73), CC/C3 Ungrouped LEW85332,48 (ID: MT-EKT-017), OC/LL6 Appley Bridge (LL6) chip pulse-laser irradiated with 20 mJ x 2 (ID: OC-TXH-012-A40), and OC/L5 Tsarev 15384,3-2 (ID: RS-CMP-065-T).

2005 NB7 has been previously identified as Sq type in [START_REF] Gietzen | IRTF observations of S complex and other asteroids: Implications for surface compositions, the presence of clinopyroxenes, and their relationship to meteorites[END_REF] with SpeX data using the Modified Gaussian Model [MGM, [START_REF] Sunshine | Estimating modal abundances from the spectra of natural and laboratory pyroxene mixtures using the modified Gaussian model[END_REF].

1994 XD

The NIR spectrum (Fig. 3.5) shows clearly an absorption around 0.9µm. The best match for this feature is for S type, followed by Cgh and Ch types, which absorption is shallow at that wavelength. The reliability of the classification is 80.4%.

When computing band parameters, the first minimum is prominent at 0.9196±0.0027 µm, and the second, less noticeable minimum is at 1.7824±0.1305µm, this implies a band separation of 0.8628µm,. Only this NIR spectrum is available, thus, solely the band minima can be computed

2007 DT 103

The best matches for this spectrum (Fig. 3 From all these meteorites, the best match for a meteorite spectrum is for Almahata Sitta.

This asteroid was already classified as a potential Q-type in DeMeo et al. [2014].

Chapter 3. Spectroscopic survey of binary asteroids

(8306) Shoko

From our analysis of this spectrum (Fig. 3.5), Shoko is a Q-type; Sq and S are also proposed, this classification has a reliability of 80.4%. When computing band parameters, the first minimum is at 0.9873±0.0085 µm, and the second minimum is at 2.0344±0.0078 µm, this implies a band separation of 1.0471 µm.

Comparing the asteroid NIR spectrum with RELAB meteorite database, the best fits for the spectra were for ordinary chondrites: Quenggouk (Sample ID: MR-MJG-042), Jelica (Sample ID: MR-MJG-072), Greenwell Springs (Sample ID: TB-TJM-075), Chateau Renard (L6) chip pulse-laser irradiated with 20 mJ energy (Sample ID: OC-TXH-011-A20), and NWA1799 (LL5) <250 µm (Sample ID: OC-SXS-026-D). [START_REF] Polishook | Observations of fresh and weathered surfaces on asteroid pairs and their implications on the rotational-fission mechanism[END_REF] classified Shoko as Sq-type using PCA on NIR spectrum obtained at IRTF/SpeX, completing the visible part with BVRI colors. From that analysis Shoko presents a fresh surface. The best proposed matches are for Xk, Cg, Cb, Ch, and K types (Fig. 3.5), a classification with a reliability of 80.4%. From inspection, there is an absorption band not considered in X or C types. Thus, the most resemblance is to K type with thermal effect.

Comparing the asteroid NIR spectrum with RELAB meteorite database, the best fits for the spectra are: Carbonaceous Chondrite PCA02012 (Sample ID: PH-D2M-044), Ordinary Chondrite Gorlovka (Sample ID: RS-CMP-048), Ordinary Chondrite Orvinio Clast & Melt (Sample ID: MP-DTB-028-C), Carbonaceous Chondrite MET00426 (Sample ID: PH-D2M-055), and Achondrite Almahata Sitta #4 chip lighter face (Sample ID: MT-PMJ-093). From all these the best match between spectra is for meteorite Gorlovka.

Previous classifications are: C-type from color indices [Pravec et al., 2000[START_REF] Dandy | Optical colors of 56 near-Earth objects: trends with size and orbit[END_REF] and from [START_REF] Yang | Observations of 2000 DP 107 in NAOC: rotation period and reflectance spectrum[END_REF] X-type based on visible spectrum and albedo.

We concatenate the visible spectrum from [START_REF] Yang | Observations of 2000 DP 107 in NAOC: rotation period and reflectance spectrum[END_REF] with the NIR spectrum. After performing the match with RELAB database found these samples: Allende 700C (Sample ID: MB-TXH-063-HD), Tsarev >300 um (ground) (Sample ID: MA-ATB-053), Orvinio Clast & Melt (Sample ID: MP-DTB-028-C), DaG 1042,05 <125 um (Sample ID: LM-H1T-052-C), and Abee 700C (Sample ID: MT-TXH-040-D). From these the best match is for Tsarev meteorite.

3.9. Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance 3.9.12 2014 WZ 120

The NIR spectrum (Fig. 3.5) shows clearly absorptions around 1 µm and 2µm. The best match for this features is for Sv type, followed by Sr and S types. The reliability of the classification is 80.4%.

When computing band parameters, the first minimum is prominent at 0.9255 ± 0.0007 µm, the second minimum is at 1.8468 ± 0.0128µm, this implies a band separation of 0.9213 µm.

Only this NIR spectrum is available, thus, solely the band minima can be computed.

Comparing the asteroid NIR spectrum with RELAB database, all the best five matches are for ordinary chondrites and all but Lancon meteorite, which is a H6 Olivine-Bronzite, are subtype H5. These are the meteorites: Ehole chip irradiated with pulse laser at 20 mJ energy x 2 (ID: OC-TXH-006-A40), Zhovtnevyi (ID: MR-MJG-041), Allegan (ID: TB-TJM-125), Magombedze (ID: TB-TJM-108), and Lancon (ID: MR-MJG-033).

(410777) 2009 FD

The NIR data (Fig. This asteroid is considered as C-type from visible colors in [START_REF] Spoto | Nongravitational perturbations and virtual impactors: the case of asteroid (410777) 2009 FD[END_REF] .

(452561) 2005 AB

This asteroid is classified inside C-complex with a reliability of 80.45%, the most akin to Cb, C, and Xk taxons (Fig. 3.5). The asteroid exhibit a thermal tail toward 2.5µm which can help us to estimate its geometrical albedo based on thermal excess approach [START_REF] Rivkin | Constraining near-Earth object albedos using nearinfrared spectroscopy[END_REF]. Our computation of the thermal excess parameter gives a value of 0.224 ± 0.011. The asteroid was observed at a distance around 1.1 a.u. having a phase angle around 50 • . The computed value of geometrical albedo 0.06 ± 0.02, which makes it compatible with low albedo taxons (C, P, T or D).

Comparing the asteroid NIR spectrum with RELAB database, the five best matches are:

(162000) 1990 OS

The spectrum (Fig. 3.5) is limited to the visible, that wavelength interval already shows the typical S-type curve. We find that the taxonomic types that better fits this spectrum are S, Sv, and L types. The reliability of the classification is 21.9% (low because of the small range considered). Even though, from inspection of this classification, the match that resembles best the spectrum of the asteroid is S type.

Comparing the asteroid visible spectrum with RELAB database, the five best matches are diverse: AC/Angrite Sahara 99555 (ID: TB-TJM-057), Si/Ol ALHA77005 olivine (+ px?) (ID: DD-MDD-009), CC/CV3 Leoville (ID: MR-MJG-120), CC/CK5-6 EET87860,14 (ID: LM-LAM-012), and Iron/IAB Silicate inclusion Campo de Cielo SI (ID: TB-TJM-059). This is understandable due to the limited data range.

(66063) 1998 RO 1

The best match is for S type -which fits very well the spectrum-followed by Sr and Sv types (Fig. 3.5). The reliability of the classification is 80.4%.

When computing band parameters, the first minimum is at 0.9221 ± 0.0031 µm, and the second minimum is at 1.8525 ± 0.0229 µm, this implies a band separation of 0.9304 µm.

Comparing the asteroid NIR spectrum with RELAB meteorite database, the best fits for the spectra were all for ordinary chondrites: OC/L5 Malakal (Sample ID: TB-TJM-109), OC/L3 Y-74191 (Sample ID: MB-TXH-084-A), OC/L6 Paranaiba (Sample ID: MB-CMP-010-L), OC/L6 Kuttippuram (Sample ID: TB-TJM-098), and OC/L5 Mirzapur (Sample ID: TB-TJM-111).

Discussion

In total, we have now 24 more binaries characterized taxonomically, representing an increase of 21% of known taxonomy classifications in the binary population, obtained with Spex/IRTF.

The analysis of all spectra was done with M4AST online tool. In this analysis we look at the taxonomy of the asteroids using χ 2 method with Bus-DeMeo taxonomy system [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] and meteorite analogues using χ 2 method with spectra from RELAB database. Ephemeris circumstances from IRTF telescope allowed us to observe very different taxonomic types of asteroids.

Having now the taxonomies of more binaries, we can look into the amount of each class of binaries among the whole population, to see if we can identify some trend, like which is more abundant (Fig. 3.10). This sample of binary asteroids is dominated by S, X and C type Chapter 3. Spectroscopic survey of binary asteroids as expected considering the binaries we characterized spectroscopically are mainly small asteroids in the near Earth space, Hungaria region, and inner belt.

Discussion

To determine if a taxonomic class (or several) is prominent among binaries, we compare our sample to the population of near-Earth and Mars-crosser asteroids analyzed by [START_REF] Carry | Spectral properties of near-Earth and Marscrossing asteroids using Sloan photometry[END_REF]. These authors indeed showed that the distribution of taxonomic classes was similar among NEAs and inner belt asteroids, in the size range we consider here. We thus compare the taxonomic distribution among binary asteroids with their corresponding background population (Fig. 3.11).

The distribution is flat for most classes but A, Q, and X. Asteroids belonging to the A class are scarce in both the inner belt space and main belt. These results are thus based on very low number statistics. The estimation of the uncertainty is still ongoing but we deem that this over representation of A type among binaries is an artifact and not significant.

Similarly, the over representation of X types is likely a selection effect. Indeed, a significant fraction of binary asteroids are located among Hungarias because they were discovered by B.

Warner's observing program dedicated to Hungarias. Photometric and spectroscopic surveys showed X type to be dominant among Hungarias [e.g., [START_REF] Gradie | Compositional structure of the asteroid belt[END_REF][START_REF] Bell | Asteroids -The big picture[END_REF][START_REF] Demeo | The taxonomic distribution of asteroids from multi-filter all-sky photometric surveys[END_REF][START_REF] Cañada-Assandri | The Hungaria population: A comparison between sub-groups[END_REF]. Moreover, the spectra of X types are mostly featureless, and noisy spectra of low contrast classes such as K or L types that could be misclassified as X types, artificially increasing the representation of X types.

By contrast, the fraction of Q types, 2.5 times more frequent than S types seems real. Finding a high fraction of Q types among small binaries was even to be expected. The most likely formation mechanism of these binaries is indeed rotational fission induced by YORP spin-up [Fig. 1.7, Walsh et al., 2008, Pravec et al., 2010[START_REF] Walsh | Formation and Evolution of Binary Asteroids[END_REF].

Figure 3.9 -Spectra of all SMASS binaries worked in this thesis. The way a bright source is detected depends on the detector, the natural one for us humans is the retina in our eyes, which is more sensitive to certain wavelengths than others, and varies among different individuals. The same happens with silver emulsions, CCDs and so on. In other words, the magnitude of a bright object depends on the detector. For this reason, we must indicate how the detection was made. The way to quantify a color of a star or an asteroid is by the difference between the magnitudes of the object in two specific wavelengths; this is know as a Color index or Color for short.

The first indications that asteroids were geologically diverse came from photometric measurements in the 1920s, with the discovery of color differences among asteroids. [START_REF] Bobrovnikoff | The spectra of minor planets[END_REF] found that Ceres was bluer than Vesta, which means that Ceres was reflecting more high-energy radiation than Vesta.

By the beginning of the 1970's the measurement of spectral reflectivity of asteroids with higher resolution became possible, this technique is called spectrophotometry. Observations of the surfaces of asteroids indicated a wide variety of compositional types. [START_REF] Mccord | Asteroid Vesta: Spectral Reflectivity and Compositional Implications[END_REF]Chapman, 1975a,b]. Little by little, the wavelength ranges were widening.

Spectroscopy became a better technique once CCDs became available, replacing photographic plates. With reflectance spectroscopy, the ratio of reflected sunlight to incident sunlight is determined as a function of wavelength. This is the most widely applied asteroid characterization technique. One advantage is that spectroscopy does not require photometric conditions, as spectrophotometry.

Colors can be considered as super low resolution spectrum. The interesting part is that it has a higher SN R for much shorter integration time, the drawback is precisely, the low resolution R λ = λ/∆λ (∆λ is the spectral resolution).

Large surveys as data sources

Although asteroid taxonomy alone is not sufficient to make meaningful mineralogical inferences, the analysis of the classes distribution in the main belt can help to highlight regions and objects that deserve further investigation for, by instance, do target selection and statistical studies.

Several efforts have been made to understand the composition of the main belt of asteroids with the aims to have insights on the formation and evolution of the Solar System [START_REF] Chapman | Surface properties of asteroids -A synthesis of polarimetry, radiometry, and spectrophotometry[END_REF][START_REF] Gradie | Compositional structure of the asteroid belt[END_REF][START_REF] Bus | Compositional structure in the asteroid belt: Results of a spectroscopic survey[END_REF], Bus and Binzel, 2002[START_REF] Mothé-Diniz | Distribution of taxonomic classes in the main belt of asteroids[END_REF]. The most recent publications presented a bias-corrected color-based taxonomy of asteroids in SDSS data to study the distribution of material in the asteroid belt according to mass, rather than number, to more accurately represent the total material in the belt [DeMeo andCarry, 2013, 2014].

The usefulness of a taxonomic scheme is proportional to the number of objects it potentially can classify. Currently are known more than 700,000 asteroids, and a million or so asteroids greater than 1 km are expected to exist in the belt according to [START_REF] Bottke | The fossilized size distribution of the main asteroid belt[END_REF]. Because several surveys detecting asteroids increase steadily the number of discovered asteroids, it is urgent to continue with this efforts in classifying asteroids.

The advantage of developing taxonomies from large photometric surveys, is that they can provide observations for much more objects than what can be obtained from spectroscopy and dedicated observing programs.

One of the large surveys that provided colors of asteroids is the Eight-Color Asteroid Survey (ECAS) [START_REF] Zellner | The eight-color asteroid survey -Results for 589 minor planets[END_REF] that obtained visible reflection spectra for 589 asteroids. In the case of spectroscopic surveys there are: the Small Main-Belt Spectroscopic Survey (SMASS) [START_REF] Xu | Small main-belt asteroid spectroscopic survey: Initial results[END_REF][START_REF] Bus | Compositional structure in the asteroid belt: Results of a spectroscopic survey[END_REF][START_REF] Burbine | Small Main-Belt Asteroid Spectroscopic Survey in the Near-Infrared[END_REF], Bus and Binzel, 2002] which measured visible spectra for 1447 asteroids; the Small Solar System Objects Spectroscopic Survey, or S 3 OS 2 [START_REF] Lazzaro | Small Solar System Objects Spectroscopic Survey: First Results[END_REF][START_REF] Lazzaro | S 3 OS 2 : the visible spectroscopic survey of 820 asteroids[END_REF]] that observed 820 asteroids. All these information led to a better understanding of minor planets. However, the results of these dedicated surveys are heavily biased towards the closest, largest, and brightest asteroids, distorting our overall picture of the asteroid belt.

In the case of large, non dedicated minor body surveys, asteroids are eventually registered in the field of view, so in order to identify the contaminators of the desired targets (stars, galaxies, extragalactic objects) it is important to discriminate the moving objects. Thus, as part of large surveys, we can have asteroid data as a by-product. This is the case of the Sloan Digital Sky Survey (SDSS) primarily designed for observations of extragalactic objects, with the SDSS Moving Object Catalog made by [START_REF] Ivezić | Color Confirmation of Asteroid Families[END_REF], that identified over 100,000 unique asteroids in five photometric bands over visible wavelengths.

Most recently, the Visible and Infrared Survey Telescope for Astronomy (VISTA), a 4m wide field

Definition of a new taxonomic scheme for NIR colors

survey telescope at Paranal Observatory. VISTA is equipped with the biggest near-infrared imaging camera (VIRCAM) operating at the 0.8-2.3µm [START_REF] Sutherland | The Visible and Infrared Survey Telescope for Astronomy (VISTA): Design, technical overview, and performance[END_REF], and among other surveys, is conducting the VISTA Hemisphere Survey (VHS1 ), currently being the largest survey conducted by the VISTA telescope. In this case, [START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF] developed a dedicated pipeline and a catalog of moving objects called MOVIS (Moving Objects VISTA Survey) to identify Solar System objects. In their article, [START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF] identified already the clustering of asteroids in color-color space, and [START_REF] Licandro | V-type candidates and Vesta family asteroids in the Moving Objects VISTA (MOVIS) catalogue[END_REF] have studied the V-type candidates in MOVIS catalog.

Motivation

We attempt to derive a new classification scheme for VISTA/VHS asteroid colors that is compatible with previous taxonomies based on spectroscopic data, mainly with [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF], which includes visible and NIR spectra, a range that covers important features to discriminate among taxonomic classes. Like previously made by [START_REF] Carvano | SDSS-based taxonomic classification and orbital distribution of main belt asteroids[END_REF] and DeMeo and Carry [2013] with SDSS visible data; but in the case of VISTA, taking advantage that in this survey we have NIR photometry, which allows to break degeneracy among taxonomic classes, in particular among silicate rich composition (S-complex). As an example, in Fig. 4.1 the average spectra for four classes are displayed, very similar if we look only the visible part of the spectra, and definitely different if we add the NIR wavelengths.

It is reasonable to define the class boundaries in a non-supervised classification (e.g. using PCA or hierarchical clustering) in order not to bias by human intervention the classification of a large data set like MOVIS. But although incomplete, our best knowledge about asteroid mineralogy comes from relating asteroid spectral taxonomic classes to meteorite spectral classes -which are samples of asteroids, thoroughly studied in laboratories-we found it is most consistent to study MOVIS low resolution data with [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy -the current standard-which in turn has been developed using PCA and was developed striving to be consistent with previous classifications, being an extension of the Bus asteroid taxonomy into the near-infrared. Thus, we can put MOVIS results in context with the findings from decades of research.

Definition of a new taxonomic scheme for NIR colors 4.2.1 Method

The methodology is based on the large database VISTA/VHS. We derived templates of the main taxonomic classes according to [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy, and use them to classify the asteroid observations.

VHS obtain images of the entire southern hemisphere using four filters in the NIR region: Y , J , H and K s [START_REF] Cross | The VISTA Science Archive[END_REF]. The band centers of these filters are located at 1.02, 1.25, 1.65 and 2.15 µm respectively (Fig. 2.18) Similarly as with SDSS, this filter set was designed for minimum superposition, and together cover a wide part of the spectral interval from 0.8 to 2.7

µm, an important range to detect diagnostic features in asteroids (Fig. 2.18). In particular, the 1 and 2 µm absorption band, diagnostic of olivine and pyroxenes assemblages, which is the prime separator of taxonomy since the earliest taxonomies in the 1970s [START_REF] Chapman | Surface properties of asteroids -A synthesis of polarimetry, radiometry, and spectrophotometry[END_REF][START_REF] Bowell | Taxonomy of asteroids[END_REF].

Data retrieval

Data was collected from MOVIS catalog [START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF] To ensure the quality of data, we remove observations that seemed unreliable (the catalog has flags relevant to photometry). We do not consider objects that were detected only with one filter. After the selection criteria we kept 7,579 asteroids out of 34,991 objects. We apply cuts in the photometry selecting error in magnitude < 0.05. From initial inspection we saw that the majority of the data was in J ,H , and K filters.

We define subsets based on the distribution on color uncertainty and construct cumulative normalized histograms to define the limits of the valid sample (Fig. 4.2). This is something empiric and chosen from the linearity of the histogram, its a trade-off between a large sample and a high SN R required for taxonomic classification. The maximum uncertainty defined The catalog does not have images in all the filters. We use always the maximum number of available colors. The degrees of freedom Do f are the total number of filters used -1. We have a maximum of 4 filters with different number of colors: 3, or 2 or 1.

Learning sample

We construct a learning sample using [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy with the VNIR reflectance spectra of the 371 asteroids that were used to create the Bus-DeMeo taxonomy, and convert it to VISTA colors. For this, we take Bus-DeMeo reflectance and multiply it with the VISTA filter transmission curves (Fig. 2.18), and take the integral, obtaining their fluxes and errors on flux. In this way we obtain colors for all the pair of filters:

Y -J , Y -H , Y -K s, J -H , J -K s, H -K s in reflectance.
But because with MOVIS we have colors, not reflectance, we have to add the colors of the Sun, somehow following the reversed path described in Fig. 2.20.

F 1 -F 2 = -2.5l og f 1 f 2 + (F 1 -F 2 ) ⊙ (4.1)
where F 1 and F 2 are magnitudes in two filters, (F 1 -F 2 ) ⊙ , is the color of the Sun with this pair of filters, and f 1 , f 2 are the fluxes in each filter. The reflectance is the spectrum divided by the spectrum of the Sun (reflectance = spectrum/spectrum ⊙ ).

Chapter 4. A new taxonomy based on NIR photometry

Similar studies [Carvano et al., 2010, DeMeo andCarry, 2013] using SDSS data took solar colors from [START_REF] Holmberg | The colours of the Sun[END_REF], who derived color estimates for the Sun in 2MASS and other photometric systems (Johnson-Cousins, Tycho, Strömgren, and SDSS) but not VISTA, besides, they did not consider the Y filter.

To determine the colors of the Sun in VISTA photometric system, we used the advantages that offers the Virtual Observatory (VO) (Sec. 2.2.8). We made a TAP3 query on VISTA survey catalogue archive for 1500 stars that have similar colors to the Sun (within ±0.1 magnitude from [START_REF] Holmberg | The colours of the Sun[END_REF] Solar color values).

Then, with VOSED4 [START_REF] Solano | VOSED: a tool for the characterization of developing planetary systems[END_REF] of the SVO 5 we retrieved the photometry of these stars from many surveys (SDSS, 2MASS, Herschel, Hipparcos, etc.) and using VOSA (SED Analyzer, [START_REF] Bayo | VOSA: virtual observatory SED analyzer. An application to the Collinder 69 open cluster[END_REF]) adjusted a synthetic stellar model called NextGen [START_REF] Kurucz | Model atmospheres for G, F, A, B, and O stars[END_REF], Allard et al., 1997[START_REF] Baraffe | Evolutionary models for metal-poor low-mass stars. Lower main sequence of globular clusters and halo field stars[END_REF], 1998[START_REF] Hauschildt | The NextGen Model Atmosphere Grid for 3000 =T e f f =10,000 K[END_REF] on the photometry; obtaining effective temperature T eff , metallicity, and gravity (log g ). After that, we select 330 solar twins (stars with same parameters as the sun). But as mentioned before, these stars are in VHS survey, we already had their colors, so we could made histograms for all of them:

Y -J , Y -H , Y -K s,
J -H , J -K s, H -K s, adjust a gaussian curve and determine mean value and uncertainty (µ ± σ) for each color (Fig. 4.3, Table 4.1). This innovative simple and powerful method can be used to obtain the colors of the Sun for any other photometric system.

Y -J , Y -H , Y -K s, J -H , J -K s, H -K s
, from that we determine mean value and uncertainty (µ ± σ, Table 4.1).

Once the data parameterization is defined, we proceed with the classification. At the beginning we attempt to use Principal component analysis, but we found that the classification could be achieved in color-color plots using the steps I will describe next. Because from MOVIS we have colors, that means that we have low resolution spectra, and the Bus-DeMeo taxonomy that we use as standard and the learning sample that we are constructing comes from [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy, developed from Visible and NIR spectra, so subtle details are lost. For this reason, instead of considering the 24 classes of [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF], we combine certain of them into their complex: C-, Cb-, Cg-, Cgh-, and Ch-types into C-complex; S-, Sa-, Sq-, Sr-, and Sv-types into S-complex; and X-, Xc-, Xe-, Xk-into X-complex. The classes that are maintained individually are A, B, D, L, K, Q, T, and V. We do not classify the particularly rare R-or O-type defined on a single object each. The list of classes considered in this work is thus: A, B, C, D, K, L, Q, S, T, V, X.

Definition of a new taxonomic scheme for NIR colors

Taxonomy scheme

We perform clustering analysis by measuring distance6 to define a metric for the taxonomy scheme. For each class and color combination, we compute the average color, the dispersion, the correlation, and the covariance. Then, in color-color space, we define ellipses with mean values of DeMeo classes as centers of coordinates, ellipse orientations angle θ are determined by the computed covariance. This maximizes the region that encompasses objects of the same class. Uncertainties σ are semimajor and semiminor axis with inclinations (Fig. 4.4), thus the ellipses are tweaked and the clustering of the objects maximized. In this way, we classify the objects by their distance µ and uncertainties σ to all the class centers, and the spread of the class, taking into account correlations between colors.

Spectral classification of asteroids serendipitously observed by VISTA

Using this tool, I inject the selected MOVIS objects and obtain the following plots in figures (4.5, 4.6), where the clustering of the different classes is remarkable.

When we have only one color (one dimension), we inspect how near to the ends it is, checking for the probability values. If it is in the middle of two classes (50% probability) it cannot be classified. But if it is close to one of the sides -depending of that probability-we can assign a taxonomy (Table 4.2). Table 4.2 -Assigned taxonomy in case of only one color.

Color

Inferior Superior

Y -J < 0.25 → B > 0.60 → V Y -H < 0.45 → B > 1.15 → A Y -K s < 0.5 → B > 1.30 → A J -H < 0.20 → V > 0.65 → A J -K s < 0.17 → V > 0.80 → A H -K s > -0.03 → V > 0.20 → D

Validation

In order to asses the quality of the classification scheme, I check the level of success in the taxonomic classification for each class. For this, I follow two paths:

1. I inject DeMeo et al. [2009] objects into the tool.Thus, I am using the learning sample to compare and explore how good the classification tool is. The output is shown in Fig. 4.7 and the fraction of valid classification in Fig. 4.8. As can be seen, there is a very good match for A, B, D and V classes. A and B classes are the most separate groups in color-color space, it is easy to identify them. Also, D and V classes are easily recognizable.

In the case of C-complex, it is ∼70% positively classified with a slight overlap with Xcomplex, the K-type overlaps with L and S types, and correspondingly some L types overlaps with K and S types. In case of Q types that are similar to S types, there is also overlap. For the S-type, there is some overlap with Q-type (they have similar spectra differencing mainly by spectral slope) and in less amount with L type. Finally, in the Xcomplex there is some overlap with C-type asteroids. In the case of T types, the match is not good. That could be because the tool does not work very well discriminating this spectrally featureless class located between the X and D-type in slope. But it is important to take into account that there are only 4 T-type asteroids out of 371 in DeMeo et al.

[2009] sample.

2. The other way to check this tool is comparing VISTA results with other sources with known taxonomy. The check I have done was with SDSS objects from DeMeo and Carry [2013] but of course the idea is to compare with all source of taxonomy. This is done as a controlled test: I know the objects that I am injecting in the scheme, and I look et al., 2016], displayed in all 15 color-color pair.

for cross-match inspecting how coherent is the proposed scheme. MOVIS classified asteroids in SDSS space is shown in Fig. 4.9. The match is good overall. C-, S-, and Vtypes are clustered and K-and L-types seems more degenerate. But as good as DeMeo and Carry [2013] work can be, we cannot suppose their others results are 100% accurate.

And most important: we have to keep in mind these are different wavelength ranges, SDSS is visible, VISTA is near infrared. With NIR wavelengths the discrimination of classes should be more complete due to the diagnostic features present in this range for several taxonomic classes, especially K,L and S types.

Results

My results are mostly quantitative, improving the statistics in asteroid taxonomy (Fig. From positive classification, the classes in the total of the sample are: 6% A-types , 1.7% are B-types, 12% are C-types, 10% are D-types, 7.6% are K-types, 16% are L-types, 9% are Q-types, 26% are S-types, 0.6% are T-types, 6% are V-types, and 5% are X-types.

As one would expect, there is a high fraction of S-complex objects. This is consistent with SDSS results [Ivezić et al., 2002, DeMeo andCarry, 2013]. S-type dominates in the Inner Main Belt, ) by number, obtained with our taxonomy scheme using MOVIS-VHS objects. It shows a similar trend as the presented in [START_REF] Gradie | Compositional structure of the asteroid belt[END_REF], in particular the trade off between dominant S in the inner belt and C in the outer belt, and Vesta family in the inner belt.

thus, there are some observing biases: because they are closer to Earth, it is easier to detect them, consequently, smaller asteroids can be detected. S-types are more easily detected also due to their high albedo of ∼0.20 [Carvano et al., 2010, DeMeo andCarry, 2013]. This is also consistent with the size-frequency distribution of smaller asteroids [START_REF] Jedicke | Observational Selection Effects in Asteroid Surveys[END_REF].

All the results presented now are preliminary and not bias-corrected. When all the classes found are represented in a plot in the space semi-major-axis vs inclination (Figs. 4.10,4.11) we found the distribution as in [START_REF] Gradie | Compositional structure of the asteroid belt[END_REF], which is comforting, and a way to validate our method. We can say that our results are consistent with decades of research (Fig. 4.12) and that we have very promising results. [1982].

Conclusions

Taxonomy is the first step to understand the distribution of bodies in the main belt of asteroids, with the aims to have insights on the formation and evolution of the Solar System. Several efforts have been made in the past from spectroscopic studies and from large photometric data analysis but in the visible only, e.g. SDSS, (and in the next future, Gaia when it release data). Now with VISTA, UKIDSS7 , and upcoming ESA Euclid8 . We have also photometric data of asteroids in the near IR.

Here we have developed a near infrared taxonomic scheme that is compatible with the [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy -the current standard-based in NIR photometry using VISTA colors of asteroids. Our scheme was constructed from a template obtained from [START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] taxonomy. The classification has been validated with asteroids with known taxonomy.

We confirm a trend seen in previous works with taxonomies, the abundance of S-type asteroids in the inner belt. In comparing our results with SDSS, at first glance we can see that the match is satisfying: C-, S-, and V-types are clustered, although K-and L-types seems more degenerate.

In this comparison we have to keep in mind that these are different wavelength ranges, SDSS is visible, VISTA is near infrared. With NIR wavelengths the discrimination of classes should be

Other Photometric Data

more complete due to the diagnostic 1µm and NIR slope features present in this wavelength range for several taxonomic classes (especially S, A, V, Q, K, L). A drawback is that the filter system we use cannot identify easily the 2 µm band.

The data was retrieved from [START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF] MOVIS-C catalog, which was developed using VISTA-VHS data release 3 (DR3) with 39,947 Solar System objects. The final Data Release is expected to have three times more objects, meaning that the expectations of improving taxonomic research are similar as what has been contributed from SDSS asteroids data.

It is important to highlight the novel way to obtain the colors of the Sun in this work, using VO advantages for search and process data of "solar twin" type stars that are present in VHS survey from all available catalogs. In perspective, compared with [START_REF] Holmberg | The colours of the Sun[END_REF] who used 9 stars, our sample has 330 solar twins, two orders of magnitude improvement.

As perspectives for future work we can mention:

1. Perform the exploitation of the database, adding new objects from future releases to continue studying the distribution of material in the asteroid belt.

2. Use the joint VIS+NIR photometry in a consistent way to better define and refine the taxonomy of asteroids.

Other Photometric Data

During the time of the thesis I was able to observe from to several facilities. These opportunities allow me to be trained with different instruments and the collection of data if the weather was benevolent.

The photometric data I gathered were colors for taxonomy and light curves for shape and binarity.

I collect light curves and colors for binaries from the Observatoire de Haute-Provence (OHP) (IAU code: 511) in the southeast of France, using the 1.20 m telescope. I also went to the Pic du Midi Observatory (IAU code: 586) in the French Pyrenees and use the 1 meter telescope (T1M) with ug r i z SDSS filters. All of the targets were binaries with no taxonomy (Table 4.3).

Also, I was included as Co-Investigator in a large program (Prog. ID 194.C-0207, PI: Pedro Lacerda), a survey for Kuiper Belt Objects (KBOs). In fact, this was the first survey of that kind for small KBOs: magnitude-limited, high-photometric-quality, high-temporal-resolution, multi-band survey of the rotational properties of over 60 Kuiper belt objects. As part of it, I was able to go observe with the New Technology Telescope (NTT, the prototype of active optics.) to La Silla Observatory at the outskirts of the Atacama Desert in Chile in January and July 2016.

This survey heas been conducted in an entirely homogeneous manner (same telescope, same

Other Photometric Data

In this respect, it is important to have in mind that KBO binaries are surprisingly abundant, particularly among Cold Classicals [START_REF] Noll | Evidence for two populations of classical transneptunian objects: The strong inclination dependence of classical binaries[END_REF] and the study of their separations, mass ratios, and surface properties can offer insights into the physics of accretion [START_REF] Nesvorný | Formation of Kuiper Belt Binaries by Gravitational Collapse[END_REF] and subsequent evolution.

This participation is also important to broaden my objects of research, having in mind that these are very correlated subjects. Also to stablish and maintain collaboration with other groups besides the French ones, keeping in mind future work from my home institution when back in Peru.

Part of the observing list at La Silla included also a comet: 67P/Churyumov-Gerasimenko, as part of a campaign of remote observations that supported the European Space Agency's Rosetta mission. My observations were included in a special issue of the Philosophical Transactions of the Royal Society of London [Snodgrass et al., 2017] .

5 Physical, spectral, and dynamical properties of (107) Camilla's triple system

Introduction

The asteroids orbiting in the main belt, between Mars and Jupiter, are the remnants of the building blocks that accreted to form terrestrial planets, left over from all the dynamical events that shaped our planetary system. If small asteroids (diameter smaller than ≈100 km) are collisionally evolved objects [START_REF] Morbidelli | Asteroids were born big[END_REF], larger bodies contain a relatively pristine record of their initial forming conditions. Decades of photometric and spectroscopic surveys, probing only the composition of the surface, have provided a clear view of the distribution of material in the inner solar system [e.g. Gradie andTedesco, 1982, DeMeo andCarry, 2014]. They, however, failed to address the original location and time scales for the accretion of these blocks, which are key to understand the processes that occurred in the disk of gas and dust around the young Sun.

Fortunately, these questions can be addressed by studying the internal structure of asteroids: objects formed far from the Sun are expected to be composed by a mixture of rocks and ices, while inner most objects are deemed volatile-free; depending on their formation time scale, the amount of radiogenic heat was different, leading to partial or complete differentiation, or not at all. With the notable exception of asteroids visited by spacecraft, density is the only physical property remotely measurable that constrains internal structure [START_REF] Scheeres | Asteroid Interiors and Morphology[END_REF]. Determination of the density relies on the measurement of the mass and the volume, and for that large asteroids with satellites are prime targets [START_REF] Carry | Density of asteroids[END_REF]. The study of their mutual orbit is currently the most precise method to estimate asteroid's masses, while they usually sustain angular diameters large enough to be spatially resolved by large telescopes, allowing the determination of their volume. Beside, the orbits of the satellites themselves offer a way to probe the gravity field, related to mass distribution inside the asteroid [START_REF] Berthier | Physical and dynamical properties of the main belt triple Asteroid (87) Sylvia[END_REF].

We focus in the present study on the outer belt asteroid (107) Camilla, discovered in the Cybele region on November 17, 1868 from Madras, India by N. R. Pogson. Its first satellite, S/2001 (107) 1, was observed for the first time in March 2001 by Storrs et al. [2001], using the Hubble Space Telescope (HST), and its orbit was first studied by [START_REF] Marchis | Main belt binary asteroidal systems with circular mutual orbits[END_REF] using observations Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system from large ground-based telescopes equipped with adaptive-optic (AO) cameras. Its second satellite, S/2016 (107) 1, was discovered in 2016 by our team [START_REF] Marsset | IAU Circular[END_REF], using the European Southern Observatory (ESO) Very Large Telescope (VLT). Gathering all the available disk-resolved and high-contrast images from HST and AO cameras, optical lightcurves, stellar occultations, and visible and near-infrared spectra (Section 5.2), we present an extensive study of the dynamics of the system (Section 5.3), of the surface properties of Camilla and its main satellite S/2001 (107) 1 (Section 5.4), and of Camilla spin and 3-D shape (Section 5.5), all constraining its physical properties (Section 5.6).

Observations

Optical lightcurves

We gather the 24 lightcurves used by [START_REF] Torppa | Shapes and rotational properties of thirty asteroids from photometric data[END_REF] to create a convex 3-D shape model of Camilla1 , compiled from the Uppsala Asteroid Photometric Catalog 2 [Lagerkvist and Magnusson, 2011]. We also retrieve the three lightcurves reported by [START_REF] Polishook | Lightcurves for Shape Modeling Obtained at the Wise Observatory[END_REF]. We complete these observations with additional lightcurves taken by our group. A total of 70 lightcurves observed between 1981 and 2016 (Table A.1) are used in this work.

High-angular resolution imaging

We compile here all the high-angular resolution images of (107) Camilla taken with the Hubble Space Telescope (HST) and large ground-based telescopes equipped with adaptive-optics (AO) cameras: Gemini North, ESO VLT, and W. M. Keck, of which only a subset had already been published [Storrs et al., 2001[START_REF] Marchis | Main belt binary asteroidal systems with circular mutual orbits[END_REF]. The images span 15 years, from March 2001 to August 2016. The images from the VLT were acquired with both the first generation instrument NACO [START_REF] Lenzen | NAOS-CONICA first on sky results in a variety of observing modes[END_REF][START_REF] Rousset | NAOS, the first AO system of the VLT: on-sky performance[END_REF] and SPHERE, the second generation extreme-AO instrument designed for exoplanet detection and characterization [START_REF] Fusco | High-order adaptive optics requirements for direct detection of extrasolar planets: Application to the SPHERE instrument[END_REF], Beuzit et al., 2008]. The images taken with SPHERE used its IRDIS differential imaging camera [START_REF] Dohlen | The infra-red dual imaging and spectrograph for SPHERE: design and performance[END_REF] sub-system. Images taken at the Gemini North used NIRI camera [START_REF] Hodapp | The Gemini Near-Infrared Imager (NIRI)[END_REF], fed by the ALTAIR AO system [START_REF] Herriot | Progress on Altair: the Gemini North adaptive optics system[END_REF]. Finally, observations at Keck were realized with the NIRC2 camera [START_REF] Van Dam | Performance of the Keck Observatory adaptive-optics system[END_REF][START_REF] Peter | Keck Observatory Natural Guide Star Adaptive Optic Facility: the first year at the telescope[END_REF]. We list in Table A.2 the details of each observation. The basic data processing (sky subtraction, bad-pixel removal, and flat-field correction) was performed using in-house routines developed in Interactive Data Language (IDL) to reduce AO-imaging data [see [START_REF] Carry | Near-infrared mapping and physical properties of the dwarf-planet Ceres[END_REF], for more details].

Observations

High-angular resolution spectro-imaging

In 2015 and 2016, we also used the IRDIFS integral-field spectrograph [START_REF] Claudi | SPHERE IFS: the spectro differential imager of the VLT for exoplanets search[END_REF] subsystem of SPHERE at the ESO VLT, aiming at measuring the reflectance spectrum of Camilla satellite S/2001 (107) 1. The observations were carried out in the IRDIFS_EXT mode, in which both IRDIS and IRDIFS observe simultaneously. In this set-up, IRDFS covers the wavelength range from 0.95 to 1.65 µm (YJH bands) at a spectral resolution of ∼30 in a 1.7 ′′ ×1.7 ′′ field of view (FoV), while IRDIS observes in the dual-band imaging mode [DBI, [START_REF] Vigan | Comparison of methods for detection and characterization of exoplanets with sphere/irdis[END_REF] with K 12 , a pair of filters in the K band (λ K 1 = 2.110 µm and λ K 2 = 2.251 µm, ∼0.1 µm bandwidth), within a 11 ′′ ×11 ′′ FoV. All observations were performed in the pupil-tracking mode, where the pupil remains fixed while the field orientation varies during the observations. This mode provides the best PSF stability and helps in reducing and subtracting static speckles noise in the images.

For the pre-processing of both the IRDIFS and IRDIS data, we made use of the preliminary release (v0.14.0-2) of the SPHERE Data Reduction and Handling (DRH) software [START_REF] Pavlov | SPHERE data reduction and handling system: overview, project status, and development[END_REF], as well as additional in-house tools written in IDL. We used the DRH for the creation of some of the basic calibrations: master sky frames, master flat-field, IRDIFS spectra positions, initial wavelength calibration and IFU flat-field. Before creating the data cubes, we used IDL routines to subtract the background to each science frame and correct for the bad pixels identified using the master dark and master flat-field DRH products. This step was introduced as a substitute to the bad pixel correction provided by the DRH. Bad pixels were first identified using a sigma-clipping routine, and then corrected performing a bicubic pixel interpolation with the MASKINTERP IDL routine. The resulting frames were then injected into the DRH recipe to create the data cubes by interpolating the data spectrally and spatially.

Stellar occultations

Eleven stellar occultations by Camilla have been observed in the last decade, mostly by amateur astronomers [see [START_REF] Mousis | Instrumental methods for professional and amateur collaborations in planetary astronomy[END_REF]. The timings of disappearance and reappearance of the stars, together with the localization of each observing station are compiled by [START_REF] Dunham | Asteroid Occultations. NASA Planetary Data System[END_REF], and publicly available on the Planetary Data System (PDS3 ). We converted the disappearance and reappearance timings of the occulted stars into segments (called chords) on the plane of the sky, using the location of the observers on Earth and the apparent motion of Camilla following the recipes by [START_REF] Berthier | Principe de réduction des occultations stellaires[END_REF]. Four stellar occultations had multiple chords, while the other events only had one or two positive chords, and provided only little constraints on the size and apparent shape of Camilla. In none of these eleven stellar occultations a secondary event was detected. We list in Table A.3 the detail of the seven events that we used (Fig. 5.7).

Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system

Near-infrared spectroscopy

On November 1, 2010, we observed Camilla over 0.8-2.5 µm with the near-infrared spectrograph SpeX [START_REF] Rayner | SpeX: A Medium-Resolution 0.8-5.5 Micron Spectrograph and Imager for the NASA Infrared Telescope Facility[END_REF], on the 3-meter NASA IRTF located on Mauna Kea, Hawaii, using the low resolution Prism mode (R = 100). We used the standard nodding procedure of observation, using alternatively two separated locations of the slit [e.g., [START_REF] Nedelcu | Near infra-red spectroscopy of the asteroid 21 Lutetia. II. Rotationally resolved spectroscopy of the surface[END_REF] to estimate the sky background. We used Spextool (SPectral EXtraction TOOL), an IDL-based data reduction package written by [START_REF] Cushing | Spextool: A Spectral Extraction Package for SpeX, a 0.8-5.5 Micron Cross-Dispersed Spectrograph[END_REF] to reduce data obtained with SpeX.

Dynamical properties

Data processing

The main challenges in measuring the position and apparent flux of the satellite of an asteroid results from their sub-arcsecond angular separation and high contrast (several magnitudes), combined with non-perfect AO correction. A typical image of a binary asteroid (Fig. 5.1) displays a central peak (the asteroid itself, angularly resolved or not) encompassed by a halo (its diffused light), within which speckle patterns appear. The faintness of these speckles produced by interferences of the incoming light make them very similar in aspect to a small moon with a contrast up to several thousands, and they can be misleading. Speckles, however, present temporal and spatial fluctuations on short timescales, depending on the ambient conditions and AO performances (e.g., seeing, airmass, brightness of the AO reference source). These fluctuations can be used to distinguish genuine satellites from speckles.

As for the direct imaging of exoplanets, it is crucial to substract the halo that surrounds the primary [in a similar way to the digital coronography of [START_REF] Assafin | Instrumental and digital coronagraphy for the observation of the Uranus satellites' upcoming mutual events[END_REF]. Because asteroids are also marginally resolved, their light is not fully coherent, and the speckle pattern is not as stable in time, nor simple, as in the case of a star. The tool we developed consider concentric annuli around the center of light of the primary to evaluate its halo. If the principle is straightforward, great caution was put in the implementation, especially in the computation of the intersection of the annuli with the pixels to allow the use of annuli with a sub-pixel width. The contribution of each pixel to different annuli is thus solved first, and the median flux of each annuli is computed, and subtracted to each pixel accordingly.

The position and flux of the satellite, relative to the primary, is then measured by fitting each time a 2-D Gaussian function to the halo-subtracted image. To estimate the uncertainties on the position and apparent flux of both the primary and the satellites, we use different apertures to fit the 2-D Gaussian function, typically from 5 to 150 pixels for the primary, and 3 to 15 for the satellites. The reported positions and apparent magnitudes (Tables A .4 and A.5) are the average of all fits (after removal of outlier values), and the reported uncertainties are the standard deviations.

Dynamical properties

Orbit determination with Genoid

We use our algorithm Genoid [GENetic Orbit IDentification, [START_REF] Vachier | Determination of binary asteroid orbits with a geneticbased algorithm[END_REF] to determine the orbit of the satellites. Genoid is a genetic-based algorithm that relies on a metaheuristic method to find the best-fit (i.e., minimum χ 2 ) suite of dynamical parameter (semi-major axis, eccentricity, etc) by refining, generation after generation, a grid of test values (called individuals).

The first generation is drawn randomly over a very wide range for each parameters, thus avoiding the miss of the global minimum from inadequate initial conditions, which is always a threat in minimization algorithms. For each individual (i.e., set of dynamical parameters), the χ 2 residuals between the observed and predicted positions is computed as

χ 2 = N i =1 X o,i -X c,i σ x,i 2 + Y o,i -Y c,i σ y,i 2 (5.1)
where N is the number of observations, and X i and Y i are the relative positions between the satellite and Camilla along the right ascension and declination respectively. The indices o and c stand for observed and computed positions, and σ are the measurement uncertainties.

A new generation of individuals is drawn by mixing randomly the parameters of individuals with the lowest χ 2 from the former generation, in a survival of the fittest fashion. This way, the entire parameter space is scanned, with the density of evaluation points increasing toward low χ 2 regions along the process. At each generation, we also use the best individual as initial condition to search for the local minimum by gradient descent. The combination of genetic grid-search and gradient descent thus ensures finding the best solution.

We then assess the confidence interval of the dynamical parameters by considering all the Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system individuals providing predictions within 1, 2, and 3 σ of the observations. The range spanned by these individuals provide the confidence interval at the corresponding σ level for each parameter.

The reliability of Genoid has been assessed during a stellar occultation by (87) Sylvia and its satellites Romulus and Remus on January 6, 2013. Genoid was used to predict the position of Romulus prior to the event, directing observers to locations specifically to target the satellite. Four different observers observed an occultation by Romulus, which was found only 13.5 km from the position predicted [START_REF] Berthier | Physical and dynamical properties of the main belt triple Asteroid (87) Sylvia[END_REF].

Orbit of S/2001 (107) 1

We measured 81 astrometric positions of the satellite S/2001 (107) 1 relative to Camilla over a span of 15 years, corresponding to 5642 days or 1520 revolutions. The orbit we derive with Genoid fits all 81 observed positions of the satellite with a root mean square (RMS) residual of 8.01 milli-arcseconds (mas) only, which corresponds to a sub-pixel accuracy.

S/2001 (107) 1 orbits Camilla on a circular, prograde, equatorial orbit, in 3.7 days with a semimajor axis of 1242 km. We detail all the parameters of S/2001 (107) 1 's orbit in Table 5.1, with their confidence interval taken at 3 σ. The distribution of residuals between the observed and predicted positions, normalized by the uncertainty on the measured positions, are plotted in Fig. 5.2. The orbit we determine here is qualitatively similar to the one by [START_REF] Marchis | Main belt binary asteroidal systems with circular mutual orbits[END_REF], while much better constrained: we fit 81 astrometric positions over 15 years with a RMS residual of 8. As a result, the mass of the system is (1.10±0.12)×10 19 kg (3 σ uncertainty range), about 1% of the mass of Ceres [START_REF] Carry | Density of asteroids[END_REF], compared with the previous reported value of (1.12 ± 0.09) × 10 19 kg.

Orbit of S/2016 (107) 1

We measured 11 astrometric positions of the satellite S/2016 (107) 1 relative to Camilla between 2015 and 2016 , corresponding to 428 days or 502 revolutions. Unfortunately, these observations correspond to only three well-separated epochs: 2015-May-29, 2016-Jul-12, and 2017-Jul-30, providing little constraint on the orbit. The orbit we derive with Genoid fits all 11 observed positions of the satellite with a RMS residual of 3.1 mas only.

S/2016 (107) 1 orbits Camilla on a plane marginally tilted (9.7 ± 8.2 • ) with respect to the equator of Camilla and S/2001 (107) 1, in 0.85 days with a semi-major axis of 507 km. Its orbit is much more eccentric than S/2001 (107) 1 's, with an eccentricity of 0.32 +0.39 -0.32 , similarly to the smaller and inner satellites of (45) Eugenia, (87) Sylvia, and (130) Elektra [START_REF] Marchis | A dynamical solution of the triple asteroid system (45) Eugenia[END_REF][START_REF] Fang | Orbits, Masses, and Evolution of Main Belt Triple (87) Sylvia[END_REF], Berthier et al., 2014, Yang et al., 2016].

We detail all the parameters of its orbit in Table 5.1, with their confidence interval taken at 3 σ. expressed in EQJ2000, obtained with Genoid: orbital period P , semi-major axis a, eccentricity e, inclination i , longitude of the ascending node Ω, argument of the pericenter ̟, time of pericenter t p . The number of observations and RMS between predicted and observed positions are also provided. We finally report the derived primary mass M , the ecliptic J2000 coordinates of the orbital pole (λ p , β p ), the equatorial J2000 coordinates of the orbital pole (α p , δ p ), and the angular tilt (Λ) with respect to the equator of Camilla. Uncertainties are given at 3-σ. We note, however, than given the very small data set consisting in three epochs only, this orbit for S/2016 (107) 1 is still preliminary and more observations are required to ascertain its orbit. The distribution of residuals between the observed and predicted positions, normalized by the uncertainty on the measured positions, are plotted in Fig. 5.3.

Dynamical properties

Surface properties

Data processing

We measured the near-infrared spectra of Camilla and its largest satellite S/2001 (107) 1 on the SPHERE/IRDIFS data. Telluric features were removed, and the reflectance spectra were obtained, by observing the nearby solar type star HD139380.

Similarly to previous sections, the bright halo of Camilla that contaminated the spectrum of the moon was removed. This was achieved by measuring the background at the location of the moon for each pixel over a 10×10-pixel region as the median value of the area defined as a 40×1-pixel arc centred on Camilla. To estimate the uncertainty and potential bias on photometry introduced by this method, we performed a number of simulations in which we injected fake companions on the 39 spectral images of the spectro-imaging cube, at separation (≈300 mas) and random position angles from the primary. The simulated sources were modeled as the PSF, from the calibration star images, scaled in contrast.

The halo from Camilla was then removed from these simulated images using the method described above, and the flux of the simulated companion measured by adjusting a 2D-Gaussian profile. Based on a total statistics of 500 simulated companions, we find that the median loss of flux at each wavelength is 11±10%. A spectral gradient is also introduced by our technique, but it is smaller than 0.06±0.07% µm -1 . The spectra of Camilla and S/2001 (107) 1 normalised at 1.1 µm are shown in Fig. 5.4.

Spectrum of (107) Camilla

Camilla was originally classified as a C type based on its visible colors and albedo [START_REF] Tedesco | Threeparameter asteroid taxonomy classifications[END_REF]. Later on, both Bus and Binzel [2002] and [START_REF] Lazzaro | S 3 OS 2 : the visible spectroscopic survey of 820 asteroids[END_REF] revised and classified it as X, based on visible spectra. More recently, based on a near-infrared spectrum from NASA IRTF Spex, [START_REF] Lindsay | Composition, mineralogy, and porosity of multiple asteroid systems from visible and near-infrared spectral data[END_REF] classified Camilla either Xe or L. We combine the near-infrared spectrum we acquired at NASA IRTF (Section 5.2.5) with the visible spectrum from SMASS [START_REF] Bus | Compositional structure in the asteroid belt: Results of a spectroscopic survey[END_REF]Binzel, 2002, Bus andBinzel, 2002] and analyze them with M4AST; using the χ 2 metric, we found Camilla to be an Xk-type asteroid (using Bus-DeMeo taxonomic scheme, Fig. 5.4). The low albedo of Camilla [0.059 ± 0.005, taken as the average of Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system the estimates by [START_REF] Morrison | TRIAD Radiometric Diameters and Albedos. NASA Planetary Data System[END_REF][START_REF] Tedesco | The Supplemental IRAS Minor Planet Survey[END_REF][START_REF] Ryan | Rectified Asteroid Albedos and Diameters from IRAS and MSX Photometry Catalogs[END_REF][START_REF] Usui | Asteroid Catalog Using Akari: AKARI/IRC Mid-Infrared Asteroid Survey[END_REF][START_REF] Masiero | Main Belt Asteroids with WISE/NEO-WISE. I. Preliminary Albedos and Diameters[END_REF] hints at a P-type classification, using the Tedesco et al.

[1989] scheme 4 . Although the best spectral match is formally found for an enstatite chondrite EH5 meteorite (Queen Alexandra Range, Antarctica origin, maximum size of 10 µm), the low albedo of Camilla argues for a different type of analog material. The composition of P-type asteroids is hard, if not impossible, to infer from their visible and near-infrared spectra owing to the lack of absorption bands.

Recently, [START_REF] Vernazza | Interplanetary Dust Particles as Samples of Icy Asteroids[END_REF] have shown that anhydrous chondritic porous interplanetary dust particules (IDPs) were likely to originate from D-and P-types asteroids, based on spectroscopic observations in the mid-infrared of outer belt D-and P-type asteroids, including Camilla. The mixture of olivine-rich and pyroxene-rich IDPs they used was compatible with the visible and near-infrared spectrum of Camilla. As such, the surface of Camilla, and more generally of D-and P-types, is very similar to that of comets, as already reported by [START_REF] Emery | Thermal emission spectroscopy (5.2 38 µm) of three Trojan asteroids with the Spitzer Space Telescope: Detection of fine-grained silicates[END_REF] from the spectroscopy of Jupiter Trojans in the mid-infrared, revealing the presence of anhydrous silicates.

Spectrum of S/2001 (107) 1

As visible on Fig. 5.4 the spectrum of S/2001 (107) 1 is very similar to that of Camilla. No significant difference in slope nor absorption band can be detected. This implies that the two components are spectraly identical from 0.95 to 1.65 µm within the precision of our measurements. Such a similarity between the components of multiple systems have already been reported for several other main-belt asteroids: (22) Kalliope [START_REF] Laver | Component-resolved near-infrared spectra of the (22) Kalliope system[END_REF], (90) Antiope [START_REF] Marchis | The origin of (90) Antiope from component-resolved near-infrared spectroscopy[END_REF], (130) Elektra [START_REF] Yang | Extreme ao observations of two triple asteroid systems with sphere[END_REF], and (379) Huenna [START_REF] Demeo | A spectral comparison of (379) Huenna and its satellite[END_REF]. Such spectral similarity, together with the main characteristics of the orbit (prograde, equatorial, circular) supports an origin of these satellites, here for S/2001 (107) 1 in particular, by impact and reaccumulation of material in orbit [see [START_REF] Margot | Asteroid Systems: Binaries, Triples, and Pairs[END_REF], for a review].

Physical properties

Data processing

We used the optical lightcurves at their face value, only converting their heterogeneous formats from many observers to the usual lightcurve inversion format [ Ďurech et al., 2010]. The location of observers together with their timings of the disappearance and the reappearance of the star were converted into chords on the plane of the sky, using the recipes from [START_REF] Berthier | Principe de réduction des occultations stellaires[END_REF]. Finally, the 2-D profile of the apparent disk of Camilla was measured on the AO images,

Physical properties

deconvolved using the Mistral algorithm [START_REF] Fusco | Correction Partielle Et Anisoplanétisme En Optique[END_REF][START_REF] Mugnier | MISTRAL: a Myopic Edge-Preserving Image Restoration Method, with Application to Astronomical Adaptive-Optics-Corrected Long-Exposure Images[END_REF] which reliability has been demonstrated elsewhere [START_REF] Witasse | Overview of the coordinated ground-based observations of Titan during the Huygens mission[END_REF], using the wavelet transform described in [START_REF] Carry | Near-infrared mapping and physical properties of the dwarf-planet Ceres[END_REF], Carry et al. [2010].

3-D shape modeling with KOALA

We used the multi-data inversion algorithm Knitted Occultation, Adaptive-optics, and Lightcurve Analysis (KOALA), which determines the set of rotation period, spin-vector coordinates, and 3-D shape that provide the best fit to all observations simultaneously [Carry et al., 2010].

The KOALA algorithm minimizes the total χ 2 = χ 2 LC + w AO χ 2 AO + w Occ χ 2 Occ that composes the individual contributions from light curves (LC), profiles from disk-resolved images (AO), and occultation chords (Occ). Adaptive optics and occultation data are weighted with respect to the light-curves with parameters w AO and w Occ respectively. The optimum values of these weights can be objectively obtained following the approach of [START_REF] Kaasalainen | Maximum compatibility estimates and shape reconstruction with boundary curves and volumes of generalized projections[END_REF].

This method has been spectacularly validated by the images taken by the OSIRIS camera on-board the ESA Rosetta mission during its flyby of the asteroid (21) Lutetia [START_REF] Sierks | Images of asteroid (21) Lutetia: A remnant planetesimal from the early Solar System[END_REF]. Before the encounter, the spin and 3-D shape of Lutetia had been determined with KOALA, using lightcurves and AO images [Carry et al., 2010]. A comparison of the pre-flyby solution with the OSIRIS images showed that the spin-vector coordinates were accurate to within 2 • , and the diameter to within 2%. That is the RMS residuals between the profiles from KOALA predictions and OSIRIS images were of only 2 km, for a 98 km-diameter asteroid [START_REF] Carry | Koala shape modeling technique validated at (21) lutetia by esa rosetta mission[END_REF].

Spin and 3-D shape of (107) Camilla

We used 70 optical lightcurves, 34 profiles from disk-resolved imaging, and 7 stellar occultation events to reconstruct the spin and 3-D shape of Camilla. The model fits very well the entire data set, with mean residuals of only 0.02 mag for the lightcurves (Fig. 5.5), 0.3 pixel for the images (Fig. 5.6), and 0.46 seconds for the stellar occultations (Fig. 5.7).

The rotation period and coordinates of the spin axis (Table 5.2) agree very well with previous results from lightcurve-only inversion and convex shape modeling [START_REF] Torppa | Shapes and rotational properties of thirty asteroids from photometric data[END_REF][START_REF] Ďurech | Combining asteroid models derived by lightcurve inversion with asteroidal occultation silhouettes[END_REF], Hanuš et al., 2016], as well as models obtained by combining lightcurves and smaller subset of present AO data [respectively 3 and 21 epochs, see [START_REF] Hanuš | Sizes of main-belt asteroids by combining shape models and Keck adaptive optics observations[END_REF][START_REF] Hanuš | Volumes and bulk densities of forty asteroids from adam shape modeling[END_REF]. The shape of Camilla is far from a sphere, with a strong ellipsoidal elongation along the equator (axes ratio of 1.39 ± 0.06 , see Table 5.2). Departures from the ellipsoid are, however, limited, and consist mainly in two large circular basins, reminiscent of impact craters (Fig. 5.8). 5.2).

Physical properties

The main features are the two deep and circular basins located at (87 • ,-23 • ) and ( 278• ,+33 • ).

The volume-equivalent diameter of Camilla is found to be 254 ± 12 km, in perfect agreement with the recent determination by [START_REF] Hanuš | Volumes and bulk densities of forty asteroids from adam shape modeling[END_REF] based on a similar data set. Both estimates are high compared to diameter estimates from infrared observations with IRAS, AKARI, or WISE [START_REF] Tedesco | IRAS Minor Planet Survey. NASA Planetary Data System[END_REF][START_REF] Ryan | Rectified Asteroid Albedos and Diameters from IRAS and MSX Photometry Catalogs[END_REF][START_REF] Usui | Asteroid Catalog Using Akari: AKARI/IRC Mid-Infrared Asteroid Survey[END_REF], Masiero et al., 2011, see Table A.6]. However, given the highly elongated shape of Camilla, it is maybe not surprising that disk-integrated mid-infrared radiometry underestimates the diameter. The agreement of the 3-D models by [START_REF] Hanuš | Volumes and bulk densities of forty asteroids from adam shape modeling[END_REF] and developed here with both the disk-resolved images and the stellar occultation timings, providing direct size measurements, indeed argues for Camilla being larger than previously thought. The corresponding volume is 8.6 ± 0.4 •10 6 km 3 , following δV /V ≈ δD/D, because the shape model is not allowed to be simply scaled in size by the data, and the uncertainties are somehow localized [see [START_REF] Kaasalainen | Shape reconstruction of irregular bodies with multiple complementary data sources[END_REF], for details].

Diameter of S/2001 (107) 1

We list in Table A.4 and display in Fig. 5.9 the 65 measured brightness difference with an uncertainty lower than 1 magnitude between Camilla and its largest satellite S/2001 (107) 1.

We found a normal distribution of measurement, as expected from photon noise, and measure an average magnitude difference of ∆m = -6.51 ± 0.27 , similar to the value of -6.31 ± 0.68 found by [START_REF] Marchis | Main belt binary asteroidal systems with circular mutual orbits[END_REF] on 22 epochs.

Using the diameter of 254 ± 12 km for Camilla (Sect. 5.5.3) and assuming S/2001 (107) 1 has the same albedo as Camilla itself (supported by their spectral similarity, see Section 5.4.3), this magnitude difference implies a size of 12.7 ± 3.4 km for S/2001 (107) 1, smaller than previously reported.

Discussion

Discussion

Density

Using the mass derived from the study of the orbit of S/2001 (107) 1, and the volume from the 3-D shape modeling, we infer a density of 1.4 ± 0.3 kg.m -3 (3 σ uncertainty), to be compared with the summary of previous reports at 2.28 ± 0.87 kg.m -3 (3 σ uncertainty) compiled by [START_REF] Carry | Koala shape modeling technique validated at (21) lutetia by esa rosetta mission[END_REF] from the mass and diameter estimates listed in Tables A.7 and A.6. Without surprise, our result is very similar to the revised density recently published by [START_REF] Hanuš | Volumes and bulk densities of forty asteroids from adam shape modeling[END_REF], who found a similar diameter. This density is consistent with the density of similar-sized asteroids in the outer belt and Trojan space, such as (617) Patroclus and (624) Hektor [START_REF] Mueller | Eclipsing binary Trojan asteroid Patroclus: Thermal inertia from Spitzer observations[END_REF], Marchis et al., 2014]. Without an unambiguous analog compound or meteorite to be used as reference, inferring the internal structure is speculative, but we can nevertheless draw certain limits. Considering the least dense meteorites in our records, the CI carbonaceous chondrites [START_REF] Consolmagno | The significance of meteorite density and porosity[END_REF], implies a porosity of 75 ± 25 %, resulting in a macroporosity of 40 ± 19 % (a random arrangement of equally sized spheres has minimum macroporosity of 26%). Considering the second least dense meteorites in our records, the CM carbonaceous chondrites [START_REF] Consolmagno | The significance of meteorite density and porosity[END_REF], implies an unrealistic porosity of 107 ± 36 %, and a macroporosity of 84 ± 46 %. This thought experiment shows that Camilla must be made of intrinsically low-density material, such as CI carbonaceous chondrites. Denser materials require more voids in its interior than matter. The low density is also consistent with the presence of ices in its interior, this low density releases some constraints on the density of the silicate phase. In all cases, the presence of fractures and voids can be expected.

123

Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system

Craters

We use the topography map (Fig. 5.8) to estimate the volume excavated from Camilla during the collisions that formed the large circular depressions. For each, we estimate the volume as the volume V c of a paraboloid as V c = π 2 d r 2 , with d the depth of the crater and r its radius.

The deeper crater at (87 • , -23 • ) has a diameter of about 80-90 km for a depth of 13-16 km (16% of diameter), accounting for a volume of 3.4-5.0 × 10 4 km 3 , equivalent to a sphere of 40-46 km in diameter. The second largest depression at (278 • , +33 • ) has a diameter of about 70 km and a depth of ≈6 km (i.e., 8% of its diameter), accounting for a volume of 1.2 × 10 4 km 3 , equivalent to a sphere of approximately 28 km in diameter.

Either of these excavations can easily account for the volume of material encompassed by the two satellites of Camilla, the diameters of which are 12.7 ± 3.4 km for S/2001 (107) 1 and 4.0 ± 1.2 km for S/2016 (107) 1 (see above). Hence, the formation of these two satellites from one of these two excavations by re-accumulation of material in orbit is probable.

The amount of material ejected by these probable impacts opens the question of a potential dynamical family linked with Camilla. Indeed, we compute that the nearby family of (87) Sylvia encompasses a comparable volume of ≈10 4 km 3 : using the Virtual Observatory tool [START_REF] Delbo | Mp 3 c: The minor planet physical properties catalogue[END_REF], we retrieve the family list of members by [START_REF] Milani | Asteroid families classification: Exploiting very large datasets[END_REF], and diameter and albedo by WISE [START_REF] Grav | WISE/NEOWISE Observations of the Hilda Population: Preliminary Results[END_REF], and compute the sum of all volumes.

MP 3 C [
Identifying such a family is, however, a complex task. As discussed by [START_REF] Vokrouhlický | Collisionally Born Family About 87 Sylvia[END_REF], the numerous mean-motion resonances with Jupiter and secular z 1 resonance [Milani andKnezevic, 1992, 1994] highly perturb the orbit of objects in the vicinity of Camilla, and these authors predict that over 2 Gyr, a family associated with Camilla would have lost 50% of its members. Moreover, the dynamical family related to (87) Sylvia, whose orbit, spectral properties, and albedo are very similar to Camilla's, blurs the picture even further.

It is possible that an ancient family linked with Camilla will be identified once the census of small (H>14) asteroids in the Cybele region grows, and colors of their surfaces will be available.

Conclusions

In the present study, we have acquired and compiled optical lightcurves, stellar occultations, visible and near-infrared spectra, and high-contrast and high-angular-resolution images and spectro-images from the Hubble Space Telescope and large ground-based telescopes (Keck, Gemini, VLT) equipped with adaptive-optics-fed cameras. (107) 1 and more eccentric. Predictions of the relative position of the satellite with respect to Camilla, critical for planning stellar occultations for instance, are available to the community through our VO service Miriade5 [START_REF] Berthier | A Service of Position and Physical Ephemerides Computation Dedicated to the Small Bodies of the Solar System[END_REF].

From the visible and near-infrared spectrum of Camilla, we classify it as an Xk-type asteroid, in the Bus-DeMeo taxonomy. Considering its low albedo, it would be classified as a P-type in older taxonomic schemes such as Tedesco's. Using VLT/SPHERE integral-field spectrograph, we measure the near-infrared spectrum of the largest satellite, S/2001 (107) 1, and compare it with Camilla. No significant difference are found. This together with its orbital parameters argue for a formation of the satellite by excavation from impact, re-accumulation of ejecta in orbit, and circularization by tides.

Using optical lightcurves, profiles from disk-resolved imaging, and stellar occultation events, we determine the spin-vector coordinates and 3-D shape of Camilla. The model fits very well each data set, and reveals two large depressions, reminiscent of impact craters. Either is large enough to be the progenitor of the satellites, and of a dynamical family, considering the comparable size of the nearby family of (87) Sylvia.

Chapter 5. Physical, spectral, and dynamical properties of (107) Camilla's triple system Figure 5.12 -Diameter estimates of (107) Camilla gathered from the literature.

Conclusions and Perspectives

Asteroids are leftovers of planetary formation, which have primordial information of the processes involved in the formation and evolution of the Solar System. In my PhD I have studied and characterized binary asteroids that serves as the closest laboratories to test properties and processes that are often difficult to probe by other means. With binaries we can obtain masses, and most importantly, densities of asteroids. That gives us information on the composition and structure of these bodies, which helps us to understand how the bodies formed. Information on the interior is something very difficult to acquire otherwise, because the majority of the information we have so far, comes from the surface of these minor bodies.

As part of my investigations I have:

1. Acquired near-infrared spectra of five binary asteroids without known taxonomy using Spex at NASA IRTF. Reduced the data and modeled the spectra to find the taxonomy and mineralogy of these binaries. I also collected 22 spectra of binary asteroids without known taxonomy from the SMASS collaboration database. I perform the modeling, find the best meteorite match from RELAB database and in this case, because I have a larger quantity, I performed a statistical analysis to find the distribution of taxonomy classes among small binaries, finding a predominance of Q-types compared with the S-types, in agreement with a formation of these systems by YORP spin-up and rotational disruption (Ch. 3).

2. Acknowledging the limitations of visible-only data (e.g SMASS and SDSS catalogs), and the difficulties to obtain large amounts of telescope time for acquiring time-consuming spectroscopy, I have worked with a large data set of near-infrared colors from VISTA VHS survey data (Ch. 4). I defined a new taxonomic scheme that will be useful for the community. Applied to VISTA data, this scheme allowed to determine the spectral class of more than 2,000 asteroids. It will open doors thanks to the future data releases from VISTA, and also Euclid and UKIDSS. Although this is a work in progress, I already obtained results that are in accordance to the previous works in the field of asteroid taxonomy, the distribution of asteroid taxonomy in the main belt I determined from Chapter 6. Conclusions and Perspectives

VISTA colors shows similar trends to those in the work by [START_REF] Gradie | Compositional structure of the asteroid belt[END_REF].

3. I have been trained in stellar occultation detections, which along with radar detection, is a direct way to measure asteroid sizes, shapes and in the cases of binaries, the distance between the bodies (asteroid and satellite).

4. I have studied throughly the binary (107) Camilla (Ch. 5 ), a ∼200 km binary asteroid.

For Camilla I have collected all available information on AO images, lightcurves, occultations and VNIR spectra to characterize its composition, density and dynamical parameters. Asteroids behave differently according to their size, so to have the big picture on binaries it is important to deal also with large asteroids. This also is important to predict occultations. In fact, the occultation campaigns I have participated in, were all for binaries with large primaries.

Among the important things I learned to acquire information, I learned to make proposals to large telescope facilities: IRTF-Spex, VLT-Xshooter. Three times, I have been granted observing time at international telescopes.

I have observed from small and large telescopes, ∼ 35 nights which includes occultations, photomometry, spectroscopy, and mineralogy. I have done the classification of large samples in order to determine physical and dynamical characteristics of binary asteroids using different tools.

Once back in Peru, I will have the task of teaching everything that I learned during this PhD. My long term plans involve forming a Solar System research group with physics students and researchers at my home institution, the Pontificia Universidad Católica del Perú. For that, I will take advantage of my on-going collaboration with european research groups, mainly with Paris Observatory's LESIA & IMCCE.

I plan to continue my research on binary asteroids, searching for more data that can give insights on this important population. I already obtained observing time at IRTF for the coming Semester 2017B for that purpose. An interesting issue is the finding about the Q/S population of small binaries that deserves more investigation and can help to refine the mechanisms that are behind the formation and evolution of these objects.

Building on my experience in observations, I plan to observe binary asteroid to obtain their multi-band photometry, i.e., colors with SDSS filters, and lightcurves, with small telescopes from Peru.

The observation of occultations has already begun via a previous collaboration with Bruno Sicardy's group (LESIA, Paris Observatory), who gave my home institution the kit to perform these observations in 2009. At that time we began with the observations, with emphasis on TNO's. We also received a FRIPON camera to install in Perú. We will be part of the world network for the detection of fireballs and recovery of meteorites. Our targets and duties have broadened. We provide here the details for each lightcurve (Table A

1. 1

 1 Asteroid belt in ǫ Eridani system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Distribution of asteroids in the Inner Solar System . . . . . . . . . . . . . . . . . 1.3 Asteroid composition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Galilean moons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Ida and Dactyl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 2014 JO25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Possible evolutionary paths of asteroids after fission . . . . . . . . . . . . . . . . . 1.8 Size of an asteroid from optical and infrared observations. . . . . . . . . . . . . . 1.9 Asteroid sizes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.10 Known binary population. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.11 Asteroids population classes definition. . . . . . . . . . . . . . . . . . . . . . . . . 1.12 Discovery statistics of PHAs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.13 Binaries in ASTORB population in the Solar System . . . . . . . . . . . . . . . . . 1.14 Planetary migration on the asteroid belt . . . . . . . . . . . . . . . . . . . . . . . 1.15 Possible formation of satellites from large impacts. . . . . . . . . . . . . . . . . . 1.16 Shoemaker Leavy-9 comet breakup . . . . . . . . . . . . . . . . . . . . . . . . . . 1.17 Mars doublet crater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.18 Itokawa rubble. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.19 Orbital elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.20 Kirkwood gaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.21 Asteroids spin rate vs. diameter from light curves. . . . . . . . . . . . . . . . . . . 1.22 Binaries-AO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.23 Asteroids spin rate vs. diameter from light curves. . . . . . . . . . . . . . . . . . . 1.24 Occultation geometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.25 Chords from an occultation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.26 Polarization of asteroids. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Atmospheric windows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Diffraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Portable telescope for occultations. . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Galilean moons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 T1M at Pic du Midi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 NTT: New Technology Telescope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii List of Figures 2.7 IRTF: Infra Red Telescope Facility . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Very Large Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 Gemini Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10 Keck Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.11 Hubble Space Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.12 The SDSS telescope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.13 The VISTA telescope on Paranal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.14 Raw and corrected images of (4666) Dietz . . . . . . . . . . . . . . . . . . . . . . . 2.15 Adaptive Optics concept. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.16 CCD scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.17 Bias and flat frames. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.18 SDSS and VISTA transmission filters . . . . . . . . . . . . . . . . . . . . . . . . . . 2.19 Interference fringes and clean image. . . . . . . . . . . . . . . . . . . . . . . . . . 2.20 The SDSS telescope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Summary of Bus DeMeo Taxonomy. . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Comparison of the different taxonomies. . . . . . . . . . . . . . . . . . . . . . . . 3.3 Undifferentiated and differentiated asteroids. . . . . . . . . . . . . . . . . . . . . 3.4 Binary asteroids without taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 NIR spectra of Sersic, Suruga, Isobe, Stephengould and 2000 RG79 . . . . . . . . 3.6 (4383) Suruga Mineralogical analysis. . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Mineralogical analysis results for (88710) 2001 SL 9 . Top Linear continuum tan-

  3.10 Contributed taxonomy -histogram . . . . . . . . . . . . . . . . . . . . . . . . . . 3.11 Taxonomies founded in this work with background small asteroid taxonomy . . 4.1 Degeneracy classes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Error cumulative histograms for defining cuts. . . . . . . . . . . . . . . . . . . . . 4.3 Histograms of G2V colors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Definition of cluster for classification in color-color space . . . . . . . . . . . . . 4.5 Results of spectral classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 VISTA MOVIS asteroid classification in J-Ks vs H-Ks . . . . . . . . . . . . . . . . . 4.7 VISTA validated with DeMeo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.8 Fraction of VISTA-DeMeo validation. . . . . . . . . . . . . . . . . . . . . . . . . . 101 xiv 1 Introduction

Figure 1 .

 1 Figure 1.2 -The asteroid population of the Solar System interior to the orbit of Jupiter. Mainbelt asteroids between Mars and Jupiter are shown in green, near-earth asteroids (NEA) are shown in red, comets are shown as blue squares, and Jupiter trojans are shown as clusters of blue dots. (Image: the Minor Planet Center.)

Figure 1 .

 1 Figure 1.6 -17-April-2017 Arecibo Radar images from contact binary 2014 JO25. Credit: JPL/NASA.

Figure 1 . 14 -

 114 Figure 1.14 -Cartoon of the effects of planetary migration on the asteroid belt based on Nice and Grand Tack models which depicts periods of radial mixing, mass removal and planet migration ultimately arriving at the current distribution of the inner Solar System. Figure from DeMeo and Carry [2014].

Figure 1 .

 1 Figure 1.20 -Kirkwood gaps. (Credit: JPL/NASA)

Figure 1 .Figure 1 .

 11 Figure 1.21 -Lightcurve of (9783) Tensho-kan. (a) Full lightcurve, (b) after substraction of the primary lightcurve, can be identified mutual events, eclipses/occultations. (c) primary rotational ligtcurve (enlarged). (Credit image:P. Pravec)

Figure 1 .

 1 Figure 1.26 -Polarization degree versus phase angle in the V and R bands for (2867) Šteins. Image from Fornasier et al. [2006].

2. 1 .

 1 Basic Concepts of Photometry which includes the Johnson, Cousins, SDSS, 2MASS, VISTA filters, etc. (Fig. 2.18).

Figure 2 . 4 -

 24 Figure 2.4 -Left: Telescope 1.20m at the Observatoire Haute Provence (OHP). Right: Camera Andor Ikon L 936 at the telescope 1.20m.(Credit: Ministère de la Culture -France).

Figure 2 . 5 -

 25 Figure 2.5 -Primary mirror and the slit of 1 meter telescope at Pic du Midi.

Figure 2 . 6 -

 26 Figure 2.6 -Image of NTT (New Technology Telescope) in between the complex of telescopes at ESO's La Silla Observatory (the third telescope from left to right.)

Figure 2

 2 Figure 2.8 -Very Large Telescope. Image: ESO.

Figure 2

 2 Figure 2.9 -Gemini Telescope. Image: www.gemini.edu.

Figure 2 . 11 -

 211 Figure 2.11 -Image of the HST as seen from the Space Shuttle Discovery during its second servicing mission. Credits: Hubblesite.org.

Figure 2 .

 2 Figure 2.12 -Left: The SDSS telescope at night. Image Credit: Patrick Galume. Right: A plot of the proper a vs. si n(i ) for 45,087 objects. The color of each dot is representative of the object's color measured by SDSS. The three main regions of the belt, defined by strong Kirkwood gaps are marked. Image from Parker et al. [2008]

Chapter 3 .

 3 Figure 3.1 -Summary of Bus DeMeo Taxonomy. Image from DeMeo et al. [2009].

Figure 3

 3 Figure 3.3 -Comparison scheme between undifferentiated and differentiated asteroids. For example, (4) Vesta survives with its original basaltic surface. When differentiated asteroids experience collisions, their crusts are stripped away and their densest Fe cores are exposed.In other cases the crusts are partially stripped away, and the exposed surfaces may be such as those visible today on the less abundant A-, E-, and R-class asteroids. Image from http: //www.cefns.nau.edu/geology/naml/Meteorite/Book-GlossaryA.html.

3. 5 .

 5 Figure 3.4 -Binary asteroids without taxonomy before current work.

  ) Stephengould, we joined the visible counterpart available in the literature [de León et al., 2010] with the NIR part of this work for the analysis (Fig. A.7).

Figure 3 . 5 -

 35 Figure 3.5 -NIR spectra of (2691) Sersic, (4383) Suruga, (7187) Isobe, (8373) Stephengould and (76818) 2000 RG79 with error-bars. Classification was made using DeMeo et al. [2009]taxonomical system, and we report the best three matches, with their χ 2 . For (4383) Suruga spectrum, five points from SDSS photometry were converted to reflectance [using the transformation by[START_REF] Bilir | Absolute magnitudes for late-type dwarf stars for Sloan photometry[END_REF][START_REF] Rodgers | Improved u'g'r'i'z' to UBVR C I C Transformation Equations for Main-Sequence Stars[END_REF] and added. Shaded in light grey are wavelength ranges affected by atmospheric absorption[START_REF] Lord | A new software tool for computing Earth's atmospheric transmission of near-and far-infrared radiation[END_REF]. All spectra are normalized to unity at 1.25 µm. Light blue corresponds to the best match spectra from RELAB library for each asteroid.

3. 8 .

 8 Figure 3.6 -(4383) Suruga Mineralogical analysis: (Left) Band Area Ratio (BAR) versus band I centers. The regions enclosed by continuous lines correspond to the values for basaltic achondrites, ordinary chondrites (OC), and olivine-rich meteorites (Ol) according to Gaffey et al. [1993]. (Right) Suruga spectrum (blue star) placed into BAR versus Band II minimum HED diagram of Moskovitz et al. [2010]. The BAR of Suruga is larger than those represented by HED's, similarly as V-type asteroids BARs in Moskovitz et al. [2010].

  Fig. 3.7 shows the VNIR composite spectrum we used to analyze with Cloutis model. The position of the centre of the two absorption bands were computed, their values are: BI min[µm] = 0.9246 ± 0.0038, BII min[µm] = 1.8727 ± 0.0087, Band separation[µm] = 0.9481. The band centers are: BI center[µm] = 0.9357 ± 0.0042, BII center[µm] = 1.8721 ± 0.0086, and the Band area ratio: 0.5858 ± 0.0019. From the analysis, the resultant mineralogy is OPX/(OPX+OL)[µm] = 0.2976 (Fig. 3.7). This means that 2001 SL 9 is an ordinary chondrite, more akin to L subtype. When comparing the asteroid VNIR spectrum with RELAB samples, the best fits of the spectra are all for ordinary chondrites: OC/LL4 Hamlet (LL4) <125 µm (Sample ID: OC-TXH-002-C), OC/L6 Chateau Renard (L6) <125 µm pellet irradiated with 5 mJ + 10 mJ laser (Sample ID: OC-TXH-011-D15), OC/H3.4 Chondrule M-H3.4-2149C (Dhajala H3.4) chondrules <125 µm (Sample ID: DP-JNG-012), OC/L5 Tsarev 15384,3-2 (Sample ID: RS-CMP-065-T) and OC/L4 Saratov (Sample ID: MB-CMP-028-B).

Figure 3 . 7 -

 37 Figure 3.7 -Mineralogical analysis results for (88710) 2001 SL 9. Top Linear continuum tangential to spectral curve of spectrum obtained after merging visible spectrum[START_REF] Lazzarin | Visible and near-infrared spectroscopic investigation of near-Earth objects at ESO: first results[END_REF] and NIR spectrum of (88710) 2001 SL 9 . Middle Wavelength position of the centers of the two absorption bands. The regions enclosed correspond to the band centers computed for the H, L, and LL chondrites. Bottom Band area ratio (BAR) versus band I center. The regions enclosed by continuous lines correspond to the values computed for basaltic achondrites (BA), ordinary chondrites (OC), and olivine-rich meteorites (Ol)[START_REF] Gaffey | Mineralogical variations within the S-type asteroid class[END_REF].

H

  =18.1 (MPC), an estimated diameter of 1.06 km.S/N of this NIR SMASS spectrum(Fig 3.9) is low, but it can be noticed a slight absorption feature at 1µm. With M4AST Classification tool using χ 2 approach based on Bus-DeMeo taxonomy[START_REF] Demeo | An extension of the Bus asteroid taxonomy into the near-infrared[END_REF] we find that the taxonomic types that best fit this spectrum are K, Cg and Ch. (Fig.3.9). The reliability of the classification is 80.4%. From inspection of these classification, the match that resembles best the spectrum of (190208) 2006 AQ is a K type. When comparing the asteroid spectrum with RELAB samples, the best fits are of different type of meteorites: Igneous meteorite Los Angeles (stone 1) (Sample ID: MT-JLB-006-B), Carbonaceous Chondrite meteorites Murchison (Sample ID: MR-MJG-109), Ordinary Chondrite meteorites Athens (LL6) chip (Sample ID: OC-TXH-013-A), Chondrite meteorites NWA753 (Sample ID: TB-TJM-114), and Chondrite meteorites A-881988,70 (Sample ID: MP-TXH-059) is obtained.

  NIR spectrum with RELAB meteorite database, the best matches are OC/L5 Olivine-Hypersthene meteorite Farmington (ID: MR-MJG-077) Achondrite Ureilite Anomalous Polymict Almahata Sitta #51 chip (ID: MT-PMJ-110), OC H3.4 M-H3.4-2149 (Dhajala H3.4) bulk <125 µm (ID: DP-JNG-011), OC H5.6 Novosibirsk dark fraction (ID: RS-CMP-049-L), and OC H3.7 ALH85121,11 (H3.7) <45 µm (ID: MT-PFV-154-A).

3. 9 .

 9 Data through The MIT-UH-IRTF Joint Campaign for NEO Spectral Reconnaissance for 1994 XD. Comparing the asteroid NIR spectrum with RELAB meteorite database, the best five matches are for these meteorites: OC/H5 Barwise (ID: MR-MJG-036), OC/L3.1 LEW86018,71 (L3.1) <45 µm (ID: MT-PFV-130-A), OC/L5 M-L5-15 (Aribba) bulk <125 µm (ID: DP-JNG-017), OC/LL3 Krymka dark powder (ID: RS-CMP-063-D), and OC/L5 Blackwell (ID: MT-HYM-081).

  been measured by Pravec et al. [2000] (U-B): 0.278, (B-V): 0.70, (V-R): 0.388 ± 0.013, (B-R): 1.088 ± 0.019, (V-I): 0.717 and Dandy et al. [2003] (B-V):0.667 ± 0.033 (V-R): 0.405 ± 0.019, (V-I): 0.687 ± 0.024, (V-Z): 0.799 ± 0.056.

  3.5), although noisy, shows an overall featureless spectrum. The best matches proposed for this spectrum are for the C complex: C, Cb and Cg types (Fig. 3.5). The reliability of the classification is 82.9%. Comparing the asteroid NIR spectrum with RELAB database, the five best matches are: KLE98300,33 (EH3) <25µm (ID: MT-PFV-122-B), Y-82162,79 <125 µm (ID: MB-CMP-019-A), Almahata Sitta #4 chip lighter face (ID: MT-PMJ-093), EET96135,20 (EH4/5) <45µm (ID: MT-PFV-120-A) and El-Quss Abu Said (CM2) <125µm (ID: MP-KHO-131-A).

  Almahata Sitta (ID: MT-PMJ-098), Rose City (ID: MR-MJG-079), Abee 900C (ID: MT-TXH-040-F), Y-74659 TXH (ID: MB-TXH-087-C), and Murchison (ID: MH-FPF-052-A). Of all these, the one that resembles more 2005 AB spectrum considering thermal emission, is Rose City meteorite, an ordinary chondrite. This is similar to the comparison made by Fieber-Beyer et al. [2015] of Chapter 3. Spectroscopic survey of binary asteroids asteroid 2007 LE.

Figure 3 . 8 -

 38 Figure 3.8 -Plot of binaries with known taxonomy (light green dots), and all-binary population (black dots) among the total asteroid population on the background.

Figure 3 .

 3 Figure 3.10 -Distribution of taxonomic classes among binary asteroids. Open bars correspond to the new classifications done within this PhD.

Figure 3 . 11 -

 311 Figure 3.11 -Ratio of the distributions of taxonomic classes among binaries over the background population [Taken from Carry et al., 2016]. Excess of A and X types are deemed spurious (see text), but that of Q/S appears genuine.

Figure 4 . 1 -

 41 Figure 4.1 -Reflectance spectra of some degeneracy classes with error barrs. Based on visible wavelengths only, A, S, K and Sa classes can hardly be distinguished. When added the NIR part of the spectra, the classes can be discriminated.

4. 2 .

 2 Definition of a new taxonomic scheme for NIR colors from all histograms are: Y -H = 0.10, Y -J = 0.075, Y -K s = 0.125, J -H = 0.125, J -K s = 0.15, H -K s = 0.15.

Figure 4 . 2 -

 42 Figure 4.2 -Cumulative normalized histogram in Y -J , Y -H , Y -K s, J -H , J -K s, and H -K s colors. Vertical line in each histogram is the maximum allowed uncertainty, that define the valid sample.

Figure 4 .

 4 Figure 4.3 -Histograms of 330 solar twins used to obtain the colors of the Sun for the learning sample based on colors from DeMeo taxonomy. Gaussian distributions are adjusted for each color histogram:Y -J , Y -H , Y -K s, J -H , J -K s, H -K s,from that we determine mean value and uncertainty (µ ± σ, Table4.1).

Figure 4 . 5 -

 45 Figure 4.5 -Result of my classification for 2,427 asteroids from VISTA MOVIS catalog[START_REF] Popescu | Near-infrared colors of minor planets recovered from VISTA-VHS survey (MOVIS)[END_REF], displayed in all 15 color-color pair.

4. 3 .

 3 Figure 4.6 -Similar to Fig. 4.5 but for J-Ks vs H-Ks only. Classification cluster around class centers defined from DeMeo et al. [2009] spectra. Asteroids without taxonomy ("U") are displayed as light grey dots in the background.

Figure 4 .

 4 Figure 4.9 -MOVIS-VISTA classified asteroids in SDSS space. This is the match between SDSS and VISTA taxonomies. The colored points are VISTA objects and the rectangles the boundaries for each class defined in DeMeo and Carry [2013].

  4.5, Fig. 4.6). The number of classified asteroids depends on the threshold on uncertainty used to select the sample.With this tool, I classified 2,427 asteroids out of 7,579 from MOVIS catalog. The unambiguous classification is the following: A-types are 149, B-types are 42, C-types are 302, D-types are 240, K-types are 185, L-types are 392, Q-types are 225, S-types are 627, T-types are 15, V-types are 134, and X-types are 116. All the other asteroids are assigned a "U" class because we could not assign a class type.

4. 3 .

 3 Figure 4.10 -Plot of classified asteroids with VISTA in semimajor axis-vs inclination space.

Figure 4 . 11 -

 411 Figure 4.11 -Histogram of the relative distribution of 3 asteroid types (S, V, C) by number, obtained with our taxonomy scheme using MOVIS-VHS objects. It shows a similar trend as the presented in[START_REF] Gradie | Compositional structure of the asteroid belt[END_REF], in particular the trade off between dominant S in the inner belt and C in the outer belt, and Vesta family in the inner belt.

Figure 4 .

 4 Figure 4.12 -Distribution of compositional types among the asteroids in the asteroid belt, it varies systematically with heliocentric distance, image adapted from[START_REF] Gradie | Compositional structure of the asteroid belt[END_REF].

Figure 5 . 1 -

 51 Figure 5.1 -Examples of AO images from Gemini, Keck, and ESO VLT. The first image (August 13, 2003, from Keck) shows a typical image, in which the halo of Camilla dominates the background and makes the satellite hard to detect. The remaining images show the result of the halo subtraction. The inner circles show the original images, in which the elongated shape of Camilla can be guessed.

  01 mas, compared to their fit of 23 positions over less than 3 years with a RMS residual of 22 mas. The much longer time span of observations provides a strict constraint on the orbital period of S/2001 (107) 1 [(3.712 ± 4 × 10 -5 )d, compared to (3.722 ± 0.003 )d from Marchis et al., 2008, hence 3.2 σ away].

Figure 5 .

 5 Figure 5.2 -Distribution of residuals between the observed (index o) and predicted (index c) positions, normalized by the uncertainty on the measured positions (σ), and color-coded by observing epoch. X stands for right ascension and Y for declination. The three large gray circles represent the 1, 2, and 3 σ limits. The top panel shows the histogram of residuals along X, and the right panel the residuals along Y. The light gray Gaussian in the background has a standard deviation of 1.

Figure 5 .

 5 Figure 5.3 -Similar as Fig. 5.2, but for S/2016 (107) 1.

Figure 5

 5 Figure 5.8 -Topographic map of Camilla, with respect to its reference ellipsoid (Table5.2). The main features are the two deep and circular basins located at (87 • ,-23 • ) and (278• ,+33 • ).

Figure 5 . 9 -

 59 Figure 5.9 -Distribution of the magnitude difference between Camilla and its largest satellite S/2001 (107) 1, compared with previous report from Marchis et al. [2008]. The dashed black line represent the normal distribution fit to our results, with a mean and standard deviation of 6.51 ± 0.27 .

Figure 5 .

 5 Figure 5.10 -Distribution of the magnitude difference between Camilla and its second satellite S/2016 (107) 1. The dashed black line represents the normal distribution fit to our results, with a mean and standard deviation of 9.0 ± 0.4 .

Figure 5 . 11 -

 511 Figure 5.11 -Mass estimates of (107) Camilla gathered from the literature.

Figure A. 1 -

 1 Figure A.1 -Reflectance spectrum of (2691) Sersic and closest matching results from meteorite comparison: a Shergottite Los Angeles (stone 1) (Sample ID MT-JLB-006-C); b LL4 ordinary chondrite Hamlet (Sample ID OC-TXH-002-A20); c Shergottite Los Angeles (Sample ID MT-JFM-005); d LL4 Amphoterite Ordinary Chondrite Soko-Banja (Sample ID MR-MJG-070); e L4 Ordinary Chondrite Barratta (Sample ID MH-CMP-002) and f) L4 Ordinary Chondrite Bjurbole unshaken (Sample ID MP-FPF-027).

Figure A. 2 -

 2 Figure A.2 -Reflectance spectrum of (4383) Suruga and closest matching results from meteorite comparison: a) achondrite Howardite Pavlovka (Sample ID MR-MJG-094); b) achondrite Basaltic HED Howardite Le Teilleul (Sample ID: MP-TXH-093-A); c) achondrite Basaltic HED howardite Frankfort howardite (Sample ID: MP-TXH-085-A); d) achondrite Basaltic HED howardite "Y-7308,142" (Sample ID: MP-TXH-097-A); e) achondrite Basaltic HED Howardite Regolith Breccia, Kapoeta P11410 (Sample ID: SN-CMP-012); and f) achondrite Basaltic HED howardite, "GRO95574,9 (Howardite) <125 um" (Sample ID: MP-TXH-125).

Figure A. 4 -

 4 Figure A.4 -Comparison of (8373) Stephengould reflectance spectrum with Relab spectra of different meteorites. (8373) Stephengould spectrum was obtained from concatenation of two spectra, the visible part from de León et al. [2010] and the NIR part from the present work. The closest matching results are for the following meteorites: a) Veramin (Sample ID MR-MJG-084), b) Butler (Sample ID MR-MJG-081), c) Pervomaisky (Sample ID RS-CMP-064), d) Tagish Lake ET01-B (Sample ID MT-MEZ-011), e) Chulafinnee (Sample ID MR-MJG-082) and f) Mundrabilla troilite (Sample ID MB-CMP-006-P2).

Figure

  Figure A.8 -(Left) (8373) Stephengould linear fit (red) of NIR spectrum points with error bars (blue). Positive slope of 0.2624 with a correlation of 0.8212. (Right) superposition of VISNIR spectrum of de León et al. [2010] from 2004 and this work NIR spectrum (2015),

Résumé

  photometry, and applied it to 30,000 asteroids from VHS survey at the ESO's telescope VISTA.

Table 3 .

 3 2 -Some characteristics of the observed asteroids: dynamical type (DT), semi-major axis (a), eccentricity (e), inclination (i), absolute magnitude (H), geometric albedo (p v ), and taxonomic classification determined in the present study.

	Object	DT	a	e	i	H	p v	Type
			(AU)		( • )
	(2691) Sersic	MB	2.24459579 0.11243958	3.594182	13.2 0.261 a	Sr
	(4383) Suruga	MB	2.42449137 0.06338279	7.153714	13.0 0.32 a	V
	(7187) Isobe	MBI 1.93746414 0.08610948	21.78856	14.0 0.134 a	K
	(8373) Stephengould	MC	3.28021862 0.55469871	40.79090	14.2	-	X b
	(76818) 2000 RG79	HUN 1.92991672 0.09576145 18.1352629 13.7	-	Xc

a From

[START_REF] Masiero | Main Belt Asteroids with WISE/NEO-WISE. I. Preliminary Albedos and Diameters[END_REF]

b The composite V+NIR spectrum was used.

Table 3 .

 3 3 -Slopes and mineralogical parameters of the spectra of binaries obtained (when possible) using Cloutis model. This asteroid was discovered on September 8, 2000, by the Lincoln Near-Earth Asteroid Research (LINEAR) program at Socorro, New Mexico. Its companion was discovered by Warner et al. [2005] from photometric observations obtained during August 7-28, 2005 at Palmer Divide Observatory (PDO) (published in

	Object	Band I Band II Band II-Band I	Slope
		(µm)	(µm)	(µm)	(Refl/µm)
	(2691) Sersic	0.9161	-	-	0.0633
	(4383) Suruga	0.9254 1.9710	1.0456	0.0616
	(7187) Isobe	1.0707	-	-	0.1571
	(8373) Stephengould	-	-	-	0.2624
	(76818) 2000 RG79	-	-	-	0.0395
	3.8.5 (76818) 2000 RG 79

Table 3 .

 3 4 -Summary of results obtained by matching the asteroids spectra with spectra from RELAB database. The comparison was made using a χ 2 method and a selection of the obtained results was done based on spectral features (band, band-gap, concavity) positions and albedo value. The figures for this comparison can be found in Appendix A.1

	Matching results for asteroids spectra

3.9.6 (399307) 1991 RJ 2

	Chapter 3. Spectroscopic survey of binary asteroids
	Comparing the asteroid NIR spectrum with RELAB meteorite database, the best five matches
	are for these meteorites: CC/CM2 Migei meteorite (ID: MA-ATB-072), CC/Laser-Irradiated
	CM Migei 4d 75-125 um meteorite (ID: MA-ATB-065), OC/L6 Pervomaisky meteorite (ID: RS-
	CMP-064), Sulfide/Troilite Mundrabilla troilite meteorite (ID: MB-CMP-006-P3), and CC/CM2
	Murchison meteorite heated at 700C (ID: MB-TXH-064-HD).
	3.9.7 (399774) 2005 NB 7
	This asteroid, an Apollo type (PHA), was discovered on July 5, 2005 from Catalina Station,
	Arizona, USA by the Catalina Sky Survey. Its companion was discovered on April 11, 2008 by
	Shepard et al. [2008] using radar observations from Arecibo Observatory, Puerto Rico.
	With an absolute magnitude of H =18.933 ± 0.545[JPL], the geometric albedo is estimated p v
	= 0.2. Primary's rotation period is 3.4883 ± 0.0001 h [Kusnirak et al., 2008], orbital period is
	15.267 ± 0.094 h [
	(399307) 1991 RJ2, an Amor type near-Earth asteroid, was discovered in September 8, 1991
	from Palomar Observatory, California, USA by Helin et al. [1991]. Its companion was discov-
	ered in August 27, 2014 by Warner et al. [2015] using lightcurve observations from Palmer
	Divide Observatory, Colorado Springs, Colorado, USA; PROMPT Telescope, Chile, and Perth
	Observatory, Australia.
	With an absolute magnitude of H = 18.9 [MPC], the primary rotation period is 3.4907 ± 0.0002
	h, and the orbital period is 15.917 ± 0.001 h. The estimated diameter of the primary is 0.5 km
	and the ratio D s/D p is > 0.47 ± 0.02. All these data are from Warner et al. [2015].
	The NIR spectrum obtained from SMASS (Fig 3.9) shows an spectrum with no features and a
	positive slope of 0.226212 ± 0.005658 Using M4AST Classification tool with χ 2 approach based
	on Bus-DeMeo taxonomy [DeMeo et al., 2009] the best match is for T type followed by X and
	Xk types (Fig. 3.5). The reliability of the classification is 80.4%.

  .5) are for Q, Sq, and S types. From all of these, Qtype matches beautifully. When computing band parameters, the first minimum is prominent at 0.9670 ± 0.0047 µm, and the second, less noticeable minimum, is at 1.9652 ± 0.0128 µm, this implies a band separation of 0.9982µm,

Comparing the asteroid NIR spectrum with RELAB meteorite database, the best fits for the spectrum were for: Laser-Irradiated Ordinary Chondrite Chateau Renard (L6) chip pulselaser irradiated with 20 mJ x 4 (Sample ID: OC-TXH-011-A80), Achondrite Almahata Sitta #44 125-500 µm (Sample ID: MT-PMJ-108-B), Ordinary Chondrite Y-74442 (Sample ID: MB-TXH-086-A), Ordinary Chondrite Appley Bridge (LL6) chip pulse-laser irradiated with 20 mJ x 2 (Sample ID: OC-TXH-012-A40), and Ordinary Chondrite Y-74646 (Sample ID: MB-TXH-085-B).

Table 3 .

 3 5 -Synthesis of asteroids characterized during this work with no previous taxonomy. These are all small asteroids. In the table are presented: dynamical type (DT), absolute magnitude (H), geometric albedo (p v ), diameter in Km (D), previous taxonomy, assigned taxonomy from this work, meteorite class and meteorite analogue. Physical characteristics of the binary asteroids: absolute magnitude, albedo, diameter, previous taxonomical class, this work taxonomical class, suitable meteorite analogue class, and best match analogue.

	Asteroid	DT	H	p v	D	Prev Tax	Our Tax	Meteorite class
	(2691) Sersic	IMB	13.4	0.261 ± 0.062	5 ± 0.11	-	Sr	OC/LL4
	(4383) Suruga	MB	12.9	0.320 ± 0.038	6.33 ± 0.09	V	V	AC/AHOW
	(7187) Isobe	HUN	6.05 ±1.46	13.89	0.134 ±0.104	-	K	AC/UAP
	(8373) Stephengould	MC	13.8	-	∼5.29	-	D	Mixture/10/90
	(76818) 2000 RG 79	HUN	13.7	0.43	∼3.6	-	Xe	enstatite chondrite
	(190208) 2006 AQ	AMO	18.1	-	1.06	-	K, Cg	Ign/She
	(348400) 2005 JF 21	AMO	17.1	∼0.59	0.3	-	V	AC/HED
	(399307) 1991 RJ 2	AMO	18.9	-	∼0.5	-	T	CC/CM2
	1994 XD	APO	19.11	-	0.6 ± 0.15	-	S	OC/H5
	2014 WZ 120	APO	20.44 ± 0.36	-	∼0.3	-	Sv	OC/H5
	(410777) 2009 FD	APO	22.1	-	0.15	-	C	EC/EH3
	(452561) 2005 AB	AMO	17.5	0.03	>1.9	-	Xk	OC/H5
	(162000) 1990 OS	APO	19.3	-	0.3 ± 0.02	-	S	AC/Angrite
	(66063) 1998 RO 1	ATE	18.1	0.14 ±0.06	0.8± 0.15	-	S	OC/L5
	(88710) 2001 SL 9	APO	17.6	-	∼0.8	Sr, Q	Sr	OC/LL4
	(162483) 2000 PJ 5	ATE	18.41± 0.05	0.2 ± 0.05	∼0.6 ± 0.1	O, Q	Q	OC/H4
	(374851) 2006 VV 2	APO	16.6 ± 0.2	-	1.06 ± 0.05	V,S,A Q,T L, Xe, Ch	OC/L5
	(399774) 2005 NB 7	APO 18.933 ±0.545	-	0.5±0.1	Sq	S Sq, S, Q	OC/L6
	2007 DT 103	APO	19.2	-	0.3	Q	Q, Sq, S	AC/UAP
	(8306) Shoko	MB	4.9	-	3.21	Sq	Q Sq S	OC/H4
	(185851) 2000 DP 107	APO	18.2	0.15 ± 0.065	0.8 ± 0.16	C, X, Sq	K, Xk Cg	OC/H3-4
	(153591) 2001 SN 263	AMO 16.861 ± 0.805 0.048 ± 0.015	2.6	B	C Cb	AC/Ureillite AP
	(285263) 1998 QE 2	AMO	17.07 ± 0.67	0.05 ± 0.03	3.2 ± 0.3	Ch	X, T, D	CC/CM2
	(481532) 2007 LE	APO	19.7	-	0.5	S	D	Stony Iron/Pallasite

Table 4 .

 4 1 -Median µ and error σ values for the colors of the Sun obtained of 330 solar twins observed by VISTA (see text, Fig. 4.3).

	Color	µ	σ
	Y-J	0.2324 0.0163
	Y-H	0.5190 0.0314
	Y-Ks 0.6015 0.0330
	J-H	0.2835 0.0216
	J-Ks	0.3651 0.0234
	H-Ks 0.0783 0.0150

Table 5 .

 5 1 -Orbital elements of the satellites of Camilla S/2001 (107) 1 and S/2016 (107) 1,

  Visible (green), near-infrared spectrum of Camilla from IRTF (deep blue and black dots) and SPHERE (red squares, offset by +0.1), and its moon S/2001 (107) 1 from SPHERE (blue triangles, offset by -0.15). Gray areas represent the wavelength ranges affected by water vapour in the atmosphere. All spectra were normalize to unity at one micron. Overplot to the IRTF spectra is the Bus-DeMeo Xk class.

						5.4. Surface properties
		1.4	(107) Camilla
	Spectral reflectance	0.8 1.0 1.2	Xk			-0.15 SpeX: Camilla SPHERE: Camilla +0.10
		0.6				SPHERE: S/2001 (107) 1 SMASS: Camilla
		0.4	0.8	1.2	1.6	2.0	2.4
				Wavelength (µm)
	Figure 5.4 -

Table 5 .

 5 2 -Sidereal rotation period, spin-vector coordinates (longitude λ, latitude β in ECJ2000), volume-equivalent diameter (D), volume (V), diameters along the principal axis of inertia (a, b, c), and axes ratio of Camilla obtained with KOALA. All uncertainties are reported at 3 σ.

	Parameter Value	Unc.	Unit
	Period	4.843927	4.10 -5	hour
	λ	69.3	9.0	deg.
	β	56.6	7.0	deg.
	T 0	2444636.00000000
	D	254.0	18.0	km
	V	8.58 •10 6	6.1 •10 5 km 3
	a	347.4	18.0	km
	b	250.6	18.0	km
	c	193.4	18.0	km
	a/b	1.39	0.09
	b/c	1.30	0.12

. Details on the observing data sets of (107) Camilla

  .1), disk-resolved image (TableA.2), and stellar occultation (TableA.3), as well as the astrometry and photometry of S/2001 (107) 1 (TableA.4) and S/2016 (107) 1 (Table A.5)TableA.1 -Date, duration (L , in hours), number of points (N p ), phase angle (α), filter, residual (against the shape model), IAU code, and observers, for each lightcurve.

			A.4Table A.1 -continued from previous page
	Date	L	N p	α	Filter RMS IAU	Observers
		(h)		( • )		(mag)
	31 2010-07-10	3.3	89 10.5 C	0.047 517 F. Reignier
	32 2010-07-11	3.1 140 10.3 C	0.041 615 J. Montier & S. Heterier
	33 2015-04-20	3.6	70	8.2 R	0.022 181 F. Vachier
	34 2015-04-21	5.7 108	7.9 R	0.020 181 F. Vachier
	35 2015-04-23	5.5	87	7.4 R	0.020 181 F. Vachier
	36 2015-04-24	6.6 118	7.2 R	0.015 181 F. Vachier
	Date 37 2015-05-09 L (h) 38 2015-05-11	N p 1.4 4.9	α 24 ( • ) 84	Filter RMS IAU 3.9 R 0.026 181 F. Vachier Observers (mag) 3.6 R 0.015 181 F. Vachier
	1981-02-01 39 2015-05-12 4.0	5 5.8	2.9 V 44 3.6 R	0.035 654 Harris and Young [1989] 0.022 181 F. Vachier
	1981-02-02 40 2015-05-13 6.2	9 5.2	2.8 V 85 3.5 R	0.030 654 Harris and Young [1989] 0.015 181 F. Vachier
	1981-02-04 41 2015-05-17 7.7	10 3.8	2.7 V 58 3.5 R	0.030 654 Harris and Young [1989] 0.018 181 F. Vachier
	1981-02-05 42 2015-05-18 5.6	14 5.8	2.8 V 89 3.6 R	0.015 654 Harris and Young [1989] 0.013 181 F. Vachier
	1982-01-09 43 2015-05-19 2.4	11 16.4 V 5.1 61 3.7 R	0.024 695 Weidenschilling et al. [1987] 0.017 181 F. Vachier
	1982-01-15 44 2015-05-20 4.4	8 16.6 V 6.0 91 3.8 R	0.027 695 Weidenschilling et al. [1987] 0.015 181 F. Vachier
	1982-05-20 45 2015-05-21 4.5	19 10.6 V 5.8 106 4.0 R	0.024 695 Weidenschilling et al. [1987] 0.016 181 F. Vachier
	1982-06-23 46 2015-05-22 4.6	6 15.8 V 5.4 98 4.1 R	0.035 695 Weidenschilling et al. [1987] 0.015 181 F. Vachier
	1982-06-24 47 2015-05-23 2.1	8 15.9 V 6.3 102 4.3 R	0.033 695 Weidenschilling et al. [1987] 0.016 181 F. Vachier
	1982-06-25 48 2015-05-24 2.9	15 16.0 V 1.0 14 4.5 R	0.023 695 Weidenschilling et al. [1987] 0.014 181 F. Vachier
	1983-03-27 49 2015-05-26 2.0	10 15.5 V 1.9 36 4.9 R	0.046 695 Weidenschilling et al. [1987] 0.018 181 F. Vachier
	1983-03-29 50 2015-06-03 4.3	5 15.4 V 3.6 68 6.8 R	0.064 695 Weidenschilling et al. [1987] 0.016 181 F. Vachier
	1983-05-24 51 2015-06-03 4.8	35 5.5 251 7.6 V 6.8 V	0.020 695 Weidenschilling et al. [1987] 0.020 517 D. Romeuf
	1983-07-03 52 2015-06-04 4.7	23 4.2	6.1 V 76 7.0 R	0.015 695 Weidenschilling et al. [1987] 0.017 181 F. Vachier
	1984-06-07 53 2015-06-05 2.2	11 14.8 V 5.0 75 7.3 R	0.053 695 Weidenschilling et al. [1987] 0.016 181 F. Vachier
	1984-06-10 54 2015-06-05 4.6	10 14.5 V 4.9 274 7.3 V	0.052 695 Weidenschilling et al. [1987] 0.020 517 D. Romeuf
	1984-07-05 55 2015-06-09 3.0	15 10.7 V 3.2 59 8.3 R	0.068 695 Weidenschilling et al. [1987] 0.020 181 F. Vachier
	1984-08-16 56 2015-06-10 5.5	32 3.0	2.3 V 38 8.5 R	0.036 809 di Martino et al. [1987] 0.019 181 F. Vachier
	1985-10-20 57 2015-06-11 4.6	21 1.4	3.0 V 27 8.7 R	0.025 695 Weidenschilling et al. [1987] 0.024 181 F. Vachier
	1987-02-06 58 2015-06-17 2.7	20 13.6 V 5.4 98 10.1 R	0.029 695 Weidenschilling et al. [1990] 0.020 181 F. Vachier
	1987-02-07 59 2015-06-20 28.2 376 10.7 R 4.7 17 13.8 V	0.037 695 Weidenschilling et al. [1990] 0.019 586 S. Fauvaud
	1988-04-25 60 2015-06-22 4.7	15 13.1 V 5.8 104 11.2 R	0.040 695 Weidenschilling et al. [1990] 0.046 181 F. Vachier
	1988-04-26 61 2015-06-23 3.6	20 13.3 V 2.2 40 11.4 R	0.034 695 Weidenschilling et al. [1990] 0.029 181 F. Vachier
	1988-04-29 62 2015-06-25 2.9	16 13.9 V 4.7 88 11.8 R	0.052 695 Weidenschilling et al. [1990] 0.021 181 F. Vachier
	2004-09-19 63 2015-06-26 6.8	15 3.8	2.0 C 70 12.0 R	0.028 A14 L. Bernasconi 0.022 181 F. Vachier
	2004-11-05 64 2015-07-06 5.6	37 13.7 C 3.8 71 13.7 R	0.052 A14 L. Bernasconi 0.020 181 F. Vachier
	2008-05-31 65 2016-04-30 1.5	44 13.5 C 1.1 19 15.5 R	0.036 181 Polishook [2009] 0.026 181 F. Vachier
	2008-06-27 66 2016-05-02 1.7	63 16.6 C 1.3 25 15.4 R	0.028 181 Polishook [2009] 0.046 181 F. Vachier
	2008-06-28 67 2016-05-03 2.0	82 16.6 C 1.4 26 15.3 R	0.023 181 Polishook [2009] 0.036 181 F. Vachier
	2010-07-09 68 2016-05-05 2.7	86 10.7 C 1.5 28 15.2 R	0.040 615 J. Montier & S. Heterier 0.044 181 F. Vachier
						Continued on next page Continued on next page

Table A .

 A 3 -Date, number of positive and negative chords (# p and # n ), average uncertainty in seconds (σ s ) and kilometers (σ k ), and RMS residuals with seconds, kilometers, and expressed in amount of standard deviation.

		Date	UT	# p # n	σ s	σ k	RMS s RMS k	RMS σ
			(h)			(s)	(km)	(s)	(km)	(σ)
	1 2004-09-05 08:54	3	0 0.73 17.831 0.860 32.358	3.277
	2 2010-09-16 04:01	1	1 0.05	0.267 0.066	0.995	1.318
	3 2015-01-01 11:26	1	2 0.22	2.445 0.017	0.975	0.077
	4 2015-02-12 11:58	2	0 0.20	6.728 1.230 22.304	8.171
	5 2015-05-06 05:23	3	4 0.33	3.831 0.389 13.324 13.219
	6 2015-08-23 04:17	6	5 0.15	4.994 0.072	8.039	2.362
	7 2016-07-21 07:42	5	5 0.56	5.060 0.579 18.920	3.067
	0	Average	-	3	2 0.32	5.880 0.459 13.845	4.499

Table A .

 A 4 -Astrometry of S/2001 (107) 1. Date, mid-observing time (UTC), telescope, camera, filter, astrometry (X is aligned with Right Ascension, and Y with Declination, and o and c indices stand for observed and computed positions), and photometry (magnitude difference ∆M with uncertainty δM ).

				A.4
	Date	UTC	Tel.	Cam.	Filter	X o	Y o	X o-c	Y o-c	σ	∆M	δM
						(mas) (mas) (mas) (mas) (mas) (mag) (mag)
	2001-03-01 05:48:13.0 HST	ACS	F439W	-573	-84	-22	3 10.00	0.00	0.00
	2001-03-01 06:00:12.9 HST	ACS	F791W	-565	-70	-20	15 10.00	0.00	0.00
	2002-05-08 10:46:01.0 Keck	NIRC2	Kp	472	-189	-2	14	9.94	6.34	1.50
	2003-06-06 14:03:06.0 Keck	NIRC2	Ks	402	-214	-4	-8	9.94	6.53	1.18
	2003-06-06 14:08:23.2 Keck	NIRC2	Ks	406	-213	1	-8	9.94	7.18	0.45
	2003-06-06 14:13:30.3 Keck	NIRC2	Ks	402	-218	0	-12	9.94	6.31	0.23
	2003-07-15 07:32:50.5 VLT	NACO	H	-540	216	6	8 27.00	6.56	0.02
	2003-07-15 07:37:26.2 VLT	NACO	H	-536	222	8	13 27.00	6.34	0.14
	2003-08-14 08:43:13.1 Keck	NIRC2	H	-249	232	10	-4	9.94	6.88	1.94
	2003-08-14 10:35:08.0 Keck	NIRC2	H	-183	227	5	-3	9.94	5.04	3.68
	2003-08-15 08:35:22.2 Keck	NIRC2	Kp	554	-62	7	-2	9.94	6.67	0.18
	2003-08-15 08:39:27.2 Keck	NIRC2	Kp	550	-66	2	-5	9.94	6.62	0.31
	2003-08-17 10:50:08.0 Keck	NIRC2	Kp	-568	146	5	3	9.94	6.55	1.21
	2003-08-17 10:53:39.3 Keck	NIRC2	Kp	-567	144	6	1	9.94	6.39	0.66
	2004-09-01 05:07:38.3 VLT	NACO	Ks	504	-164	7	1 13.24	6.06	0.31
	2004-09-01 05:17:22.2 VLT	NACO	H	510	-165	8	0 13.24	6.34	0.24
	2004-09-01 08:06:43.4 VLT	NACO	Ks	576	-169	11	-1 13.24	6.98	0.43
	2004-09-03 06:51:57.5 VLT	NACO	Ks	-623	166	-25	2 13.24	6.76	0.70
	2004-09-05 04:28:20.2 VLT	NACO	Ks	624	-163	9	0 13.24	6.73	0.09
									Continued on next page

. Details on the observing data sets of (107) Camilla

					Table A.4 -continued from previous page Table A.4 -continued from previous page
	Date	Date	UTC	UTC Tel.	Tel. Cam.	Cam. Filter	Filter X o	X o Y o	Y o X o-c	X o-c Y o-c	Y o-c σ	σ ∆M	∆M δM
							(mas) (mas) (mas) (mas) (mas) (mag) (mas) (mas) (mas) (mas) (mas) (mag) (mag)
	2004-09-08 06:41:20.2 VLT 2015-05-29 04:51:27.2 VLT SPHERE Ks NACO	Ks		-180	211 241	-120	1	5	-9 13.24 0 12.26 6.26	6.95 0.09
	2004-09-11 04:34:26.2 VLT 2015-05-29 05:07:36.3 VLT SPHERE YJH NACO	Ks		-164	-539 241	87	5	-8	0	-10 13.24 7.40 6.35	7.09 0.09
	2004-09-13 03:42:52.5 VLT 2015-05-29 05:07:36.3 VLT SPHERE Ks NACO	Ks		-166	470 245	-75	3	1	1 13.24 3 12.26 6.26	7.23 0.06
	2004-09-13 05:47:28.2 VLT 2015-05-29 05:15:13.1 VLT SPHERE YJH NACO	Ks		-157	386 242	-46	5	-16	0	7 13.24 7.40 6.43	6.08 0.30
	2004-09-14 04:09:30.3 VLT 2015-05-29 05:15:13.1 VLT SPHERE Ks NACO	Ks		-158	-500 245	153	5	-13	-1 13.24 3 12.26 6.35	6.59 0.17
	2004-09-15 04:18:34.3 VLT 2015-05-29 05:25:55.5 VLT SPHERE Ks NACO	Ks		-152	-321 245	35	3	-2	4 13.24 2 12.26 6.36	6.28 0.16
	2004-09-15 04:26:56.5 VLT 2015-05-29 05:28:59.5 VLT SPHERE YJH NACO	H		-148	-315 243	36	4	-2	0	6 13.24 7.40 6.49	7.30 0.16
	2004-10-07 02:02:03.0 VLT 2015-05-29 05:28:59.5 VLT SPHERE Ks NACO	Ks		-150	-540 247	123	3	1	-5 13.24 3 12.26 6.34	8.49 0.08
	2004-10-08 02:22:38.3 VLT 2015-05-29 05:32:04.0 VLT SPHERE YJH NACO	Ks		-146	356 243	-106	4	5	0	0 13.24 7.40 6.51	8.22 0.17
	2004-10-08 04:47:21.2 VLT 2015-05-29 05:32:04.0 VLT SPHERE Ks NACO	Ks		-148	435 245	-125	2	5	-1 13.24 1 12.26 6.42	7.07 0.09
	2004-10-20 00:39:22.2 VLT 2016-07-02 08:47:22.2 VLT SPHERE YJH NACO	Ks		-279	553 -90	-136 -7	9 -3	0 13.24 7.40 6.68	6.55 0.28
	2004-11-02 07:36:13.0 Gemini NIRI 2016-07-12 05:04:19.4 VLT SPHERE YJH	Kp		601	-344 -129	88 -7	-3	1	0 21.90 7.40 6.55	6.49 0.19
	2004-11-02 07:38:36.9 Gemini NIRI 2016-07-12 05:11:41.7 VLT SPHERE YJH	Kp		601	-340 -130	90 -7	0	1	2 21.90 7.40 6.51	6.40 0.06
	2004-11-05 08:09:18.1 Gemini NIRI 2016-07-12 05:19:03.9 VLT SPHERE YJH	Kp		601	-538 -129	138 -7	-9	4	2 21.90 7.40 6.49	5.95 0.03
	2005-12-21 09:05:51.5 Gemini NIRI 2016-07-28 05:50:56.0 VLT SPHERE YJH	Ks		-208	684 -138	0	5	11 -4	-4 21.90 7.40 6.96	6.53 0.24
	2006-01-01 10:17:12.1 Gemini NIRI 2016-07-28 05:57:12.3 VLT SPHERE YJH	Ks		-212	651 -137	-35	6	9 -5	-5 21.90 7.40 7.10	6.71 0.06
	2006-01-09 05:20:11.1 Gemini NIRI 2016-07-28 06:03:30.1 VLT SPHERE YJH	Ks		-216	557 -135	116	6	18 -5	3 21.90 7.40 7.07	5.86 0.19
	2006-01-16 05:16:51.5 Gemini NIRI 2016-07-30 01:37:12.1 VLT SPHERE YJH	Ks		192	619 141	-17 -1	25	0	33 21.90 7.40 6.90	5.85 0.20
	2009-06-07 10:29:14.1 Keck 2016-07-30 01:44:17.2 VLT SPHERE YJH NIRC2	H		194	510 135	54 -4	1 -3	-1 7.40	9.94 6.78	6.56 0.23
	2009-06-07 10:32:18.1 Keck 2016-07-30 01:51:22.2 VLT SPHERE YJH NIRC2	H		199	511 135	55 -4	1 -2	0 7.40	9.94 6.65	6.49 0.44
	2009-06-07 10:54:08.0 Keck 2016-08-11 00:18:43.4 VLT SPHERE YJH NIRC2	Kp		579	516 -159	55 -7	-2	6	7 7.40	9.94 6.18	6.23 0.07
	2009-06-07 11:23:04.0 Keck 2016-08-11 02:41:34.1 VLT SPHERE YJH NIRC2	Kp		559	530 -189	44 -3	0	5	5 7.40	9.94 6.54	6.56 0.23
	2009-06-07 11:25:56.5 Keck 2016-08-11 02:48:41.5 VLT SPHERE YJH NIRC2	Kp		560	530 -189	39 -1	0	6	0 7.40	9.94 6.43	6.66 0.08
	2009-08-16 06:47:02.0 Keck 2016-08-11 02:55:50.8 VLT SPHERE YJH NIRC2	FeII	556	-36 -194	239 -3	6	1	1 7.40	9.94 6.43	6.99 0.07
	2010-08-15 08:07:02.0 Gemini NIRI	Kp			-421 Average	182	1	-2	1	14 21.90 18 6.50	5.84 0.48
	2010-08-15 08:16:53.5 Gemini NIRI	Kp	-412 Standard deviation 8 181	1	7	13 21.90 7 0.28	6.40 0.63
	2010-08-28 08:49:11.1 Gemini NIRI	Kp			379	-189		0	-14 21.90	6.05
	2010-08-28 08:54:01.0 Gemini NIRI	Kp			378	-186		1	-11 21.90	6.52
	2010-09-02 06:45:32.3 Gemini NIRI	Kp			-588	157		-7	10 21.90	6.02
	2010-10-31 05:58:48.4 Gemini NIRI	Kp			-271	-8		24	-8 21.90	6.67
	2010-10-31 06:03:23.2 Gemini NIRI	Kp			-290	-2		7	-2 21.90	6.87
	2011-09-27 05:04:41.0 VLT	NACO	H			-287	236		2	13 13.24	6.39
	2011-09-29 05:21:18.1 VLT	NACO	H			440	-217		-1	-8 13.24	7.04
	2011-11-08 03:21:35.3 VLT	NACO	H			-438	-61		-9	0 13.24	6.66
	2011-11-10 01:22:04.0 VLT	NACO	H			386	93		5	19 13.24	7.35
	2015-05-29 04:38:46.4 VLT	SPHERE YJH		-184	237		6	-2	7.40	6.28
	2015-05-29 04:38:46.4 VLT	SPHERE Ks			-188	240		2	0 12.26	6.29
	2015-05-29 04:51:27.2 VLT	SPHERE YJH		-176	239		4	0	7.40	6.30
														Continued on next page

Table A .

 A 5 -Astrometry of S/2016 (107) 1. Date, mid-observing time (UTC), telescope, camera, filter, astrometry (X is aligned with Right Ascension, and Y with Declination, and o and c indices stand for observed and computed positions), and photometry (magnitude difference ∆M with uncertainty δM ).

				A.4
	Date	UTC	Tel. Cam.	Filter	X o	Y o	X o-c	Y o-c	σ	∆M	δM
					(mas) (mas) (mas) (mas) (mas) (mag) (mag)
	2015-05-29 04:38:46.4 VLT SPHERE YJH	87	140	1	1	7.40	8.95	1.40
	2015-05-29 04:51:27.2 VLT SPHERE YJH	102	141	4	2	7.40	8.65	0.25
								Continued on next page

. Details on the observing data sets of (107) Camilla

		A.5
			Table A.5 -continued from previous page
	Date	UTC	Tel. Cam.	Filter	X o	Y o	X o-c	Y o-c	σ	∆M	δM
					(mas) (mas) (mas) (mas) (mas) (mag) (mag
	2015-05-29 05:07:36.3 VLT SPHERE YJH	111	137	-1	-1	7.40	8.43	1.53
	2015-05-29 05:15:13.1 VLT SPHERE YJH	121	142	1	3	7.40	8.66	0.60
	2015-05-29 05:32:04.0 VLT SPHERE YJH	135	136	0	-1	7.40	8.83	1.59
	2016-07-12 05:04:19.4 VLT SPHERE YJH	-271	115	7	-2	7.40	9.16	0.82
	2016-07-12 05:11:41.7 VLT SPHERE YJH	-275	113	0	-6	7.40	9.53	1.23
	2016-07-12 05:19:03.9 VLT SPHERE YJH	-272	119	0	-2	7.40	9.34	0.95
	2016-07-30 01:37:12.1 VLT SPHERE YJH	-295	104	-1	5	7.40	9.32	0.33
	2016-07-30 01:44:17.2 VLT SPHERE YJH	-295	103	-3	2	7.40	9.23	0.20
	2016-07-30 01:51:22.2 VLT SPHERE YJH	-288	102	0	-1	7.40	9.53	1.69
						Average	0	0	10	9.05	0.96
					Standard deviation 3	3	0	0.32	0.56

. Previous determinations of mass and diameter of (107) Camilla Table

  A.7 -The mass estimates (M ) of (107) Camilla collected in the literature. For each, the uncertainty, method, selection flag, and bibliographic reference are reported. The methods are BGENO: Binary: Genoid, BIMG: Binary: Imaging, DEFL: Deflection, EPHEM: Ephemeris.

	#	Mass (M )	Method Sel.	Reference
		(kg)
	1	(1.12 ± 0.03) × 10 19 BIMG	✓ Marchis et al. [2008]
	2	(3.62 ± 0.92) × 10 19 EPHEM	✗	Fienga et al. [2010]
	3 4	3.88 +10.90 -3.88 × 10 18 DEFL (3.90 ± 1.06) × 10 19 DEFL	✓ Zielenbach [2011] ✗ Zielenbach [2011]
	5 (17.60 ± 8.69) × 10 18 DEFL	✓ Zielenbach [2011]
	6 7	2.25 +18.00 -2.25 × 10 18 DEFL (2.71 ± 0.70) × 10 19 EPHEM	✓ Zielenbach [2011] ✗ Fienga et al. [2011]
	8	(6.79 ± 3.00) × 10 18 EPHEM	✓ Fienga et al. [2013]
	9 (11.10 ± 1.79) × 10 18 DEFL	✓ Goffin [2014]
	10 (16.10 ± 9.13) × 10 18 EPHEM	✓ Fienga (priv. comm.)
	11	(1.20 ± 0.15) × 10 19 BGENO	✓ This work
		(11.03 ± 2.11) × 10 18	Average

in a similar way as currently is being investigated in ǫ Eridani system.

AU -Astronomical Unit: the mean distance of Earth from the Sun = 1.496×10 11 m

and also another between Venus and Mercury

now numbered in order of discovery: (1) Ceres, (2) Pallas, (3) Juno, (4) Vesta, all women!...not anymore

The first 25 asteroids discovered during the half month period September 1-15 in 1991 will be numbered 1991 RA to 1991 RZ. The next 25 will be numbered 1991 RA 1 to 1991 RZ 1 , subsequent discoveries in that period the subscript number will be 2, 3, 4,... etc.

https://www.iau.org/public/themes/naming/#minorplanets

http://www.boulder.swri.edu/merline/petitprince.name.txt

Not actual telegrams, the name was kept for historical reasons.

http://www.cbat.eps.harvard.edu/minorsats.html

http://www.asu.cas.cz/ ppravec/

https://obswww.unige.ch/~behrend/page_cou.html

The secondary-to-primary size ratio D s/D p is an important quantity in binary systems.[START_REF] Pravec | Photometric survey of binary near-Earth asteroids[END_REF] identified two effects limiting sizes of binary system components. One effect is that Ds/Dp ratios appear to concentrate below Ds/Dp = 0.5. Satellites larger than 0.5 Dp appear rare in asynchronous binary NEA systems. Binary systems with Ds/Dp > 0.18 appear to concentrate among NEAs with Dp < 2 km.

https://cneos.jpl.nasa.gov/about/neo_groups.html

http://www.minorplanetcenter.net/iau/lists/t_phas.html

http://johnstonsarchive.net/astro/asteroidmoons.html

Rubble-pile asteroids are defined as a collection of gravitationally self-bound components ranging in size from micrometers to kilometer size fragments.

a sphere of the same total mass and volume as the two components of the binary system

Recalled in Asteroids III and Asteroids IV

it has a twin -Gemini South-in Cerro Pachón, Chile

http://vo.imcce.fr/webservices

http://vo.imcce.fr/webservices/skybot/index.php

mirror is tilted at the tip in order to correct the distorted wavefront.

or photon noise, which is an uncertainty associated with the measurement of light inherent to its quantized nature. It has a Poisson distribution.

We refer here only to the reflection spectral behaviors.

http://irtfweb.ifa.hawaii.edu/cgi-bin/spex/find_a0v.cgi

A cycle commands a beam-switch sequence, in case AB, 2 images are taken.

http://m4ast.imcce.fr/

http://www.planetary.brown.edu/relab/

Defined as the ratio of the number of points of the asteroid spectrum over the total number of points defined for the taxonomic type.

D s: Diameter of secondary, D p: Diameter of primary

Using the dynamical class in vo.imcce.fr

https://neat.jpl.nasa.gov/

http://www.astro.unipd.it/planets/sineo.html

https://echo.jpl.nasa.gov/asteroids/2006VV2/2006VV2_planning.html

http://www.vista-vhs.org/

http://cdsarc.u-strasbg.fr/viz-bin/Cat

Table Access Protocol

a Virtual Observatory tool to build and analyze SEDs (Spectral Energy Distributions) developed in the framework of the Spanish

VO 5 Spanish Virtual Observatory, http://sdc.cab.inta-csic.es/vosed/

in color-color space

the next generation near-infrared sky survey, successor to 2MASS, http://www.ukidss.org/

a space mission to map the geometry of the dark Universe, which will produce also a massive legacy of deep images and spectra over at least half of the entire sky with spatial resolution of 0.2 seconds of arc. http: //sci.esa.int/euclid/

Available on DAMIT[ Ďurech et al.,

2010]: http://astro.troja.mff.cuni.cz/projects/asteroids3D/ 2 http://asteroid.astro.helsinki.fi/apc/asteroids/

http://sbn.psi.edu/pds/resource/occ.html

The X-complex is characterized by moderately sloped and featureless spectra, it is compositionally degenerate because it comprises asteroids with different albedos. The[START_REF] Tholen | Asteroid taxonomy from cluster analysis of photometry[END_REF] taxonomy distinguished the X-complex by albedo, breaking it up into the E, M, and P classes that ranged from high to low albedo.

http://vo.imcce.fr/

Remerciements

In order to place constraints on planetesimal accretion mechanisms and time-scales, effects of collisional evolution, the effects of strong early dynamical evolution in our planetary system and also, matching the theme of my current work, allow for comparisons with main-belt asteroids and Trojans.

A An appendix

A.1 Asteroid spectra vs meteorites spectra is very hard to do. Using M4Ast we obtain the first minimum BI at 0.9161±0.0050 µm, the second minimum BII is at 2.2718±0.0050 µm, however this part of the data is too nosy to trust that position. There are also spectral variations around 1.45 µm and 1.9 µm due to the influence of telluric water that remained after the data reduction.

A.2 Asteroid Band parameters

A.3 (8373) Stephengould spectrum Analysis

Appendix A. An appendix

A.4. Details on the observing data sets of (107) Camilla

A.5 Previous determinations of mass and diameter of (107) Camilla