Cristian Ruiz
email: cristian.ruiz@imag.fr

Olivier Richard
email: olivier.richard@imag.fr

Joseph Emeras
email: joseph.emeras@imag.fr

Reproducible Software Appliances for Experimentation

Keywords: Reproducible Research, Testbed, Virtual Appliances, Cloud Computing, Experiment Methodology

Experiment reproducibility is a milestone of the scientific method. Reproducibility of experiments in computer science would bring several advantages such as code re-usability and technology transfer. The reproducibility problem in computer science has been solved partially, addressing particular class of applications or single machine setups. In this paper we present our approach oriented to setup complex environments for experimentation, environments that require a lot of configuration and the installation of several software packages. The main objective of our approach is to enable the exact and independent reconstruction of a given software environment and the reuse of code. We present a simple and small software appliance generator that helps an experimenter to construct a specific software stack that can be deployed on different available testbeds.

Introduction

In order to strengthen the results of a research it is important to carry out the experimental part under real environments. In some cases, these real environments consist in a complex software stack that normally comprises a configured operating system, kernel modules, run-time libraries, databases, special file systems, etc. The process of building those environments has two shortcomings: (a) It is a very time consuming task for the experimenter that depends on his/her expertise. (b) It is widely acknowledged that most of the time, it is hardly reproducible. A good practice at experimenting is to assure the reproducibility. For computational experiments this is a goal difficult to achieve and even a mere replication of the experiment is a challenge [START_REF] Davison | Automated capture of experiment context for easier reproducibility in computational research[END_REF]. This is due to the numerous details that have to be taken into account. The process of repeating an experiment was carefully studied in [START_REF] Clark | Xen and the art of repeated research[END_REF] and among the many conclusions drawn, the difficulty of repeating published results was highly relevant.

With the advent of testbeds such as Grid'5000 [START_REF] Cappello | Grid'5000: a large scale, reconfigurable, controlable and monitorable Grid platform[END_REF] and FutureGrid [START_REF] Laszewski | Design of the futuregrid experiment management framework[END_REF], cloudbased testbeds like BonFIRE 1 , the ubiquity of Cloud computing infrastructures and the virtualization technology that is accessible to almost anyone that has a computer with modest requirements. Now it is possible to deploy virtual machines or operating system images, which makes interesting the approach of software appliances for experimentation. In [START_REF] Howe | Virtual appliances, cloud computing, and reproducible research[END_REF] the author gives 13 ways that replicability is enhanced by using virtual appliances and virtual machine snapshots. Another close approach is shown in [START_REF] Dudley | In silico research in the era of cloud computing[END_REF] where snapshots of computer systems are stored and shared in the cloud making computational analysis more reproducible. A system to create executable papers is shown in [START_REF] Brammer | Paper mch: Creating dynamic reproducible science[END_REF], which relies on the use of virtual machines and aims at improving the interactions between authors, reviewers and readers with reproducilibity purposes.

Those approaches offer several advantages such as simplicity, portability, isolation and more importantly an exact replication of the environment but they incurred in high overheads in building, storing and transferring the final files obtained. Additionally, it is not clear the composition of the software stack and how it was configured. We lose the steps that let to their creation.

In this paper, we present our approach to reproduce a software environment for experimentation. The approach is based on a software appliance generator called Kameleon. We present the implementation of a persistent cache mechanism that stores every piece of data (e.g., software packages, configuration files, scripts, etc.) used to construct the software appliance. It presents a lightweight approach which enables the construction and exact post reconstruction of a given software appliance from text descriptions. Kameleon persistent cache mechanism presents three main advantages: (1) it can be used as a format to distribute and store individual and related software appliances (virtual cluster) incurring in less storage requirements; (2) provenance of data, anyone can look at the steps that led to the creation of a given experimental environment; (3) it helps to overcome widespread problems occasioned by small changes in binary versions, unavailability of software packages, changes in web addresses, etc. This paper is structured as follows: In Section 2, some approaches to reproduce a given environment for experimentation are discussed. Then, our approach to set up the environment required for experimentation is described in Section 3. In Section 4, we show some experimental results and validation of our approach. Finally the conclusions are presented in Section 5.

Related works

Experimenters have different options to make the environment for experimentation more reproducible. They can capture the environment where the experiment was run or they can use a more reproducible approach to set up the experiment from the beginning.

Tools for capturing the environment of experimentation

CDE [START_REF] Guo | Cde: run any linux application on-demand without installation[END_REF] and ReproZip [START_REF] Chirigati | Reprozip: using provenance to support computational reproducibility[END_REF] are based on the capture of what it is necessary to run the experiment. They capture automatically software dependencies through the interception of Linux system calls. A package is created with all these dependencies enabling it to be run on different Linux distributions and versions. ReproZip unlike CDE allows the user to have more control over the final package created. Both tools provide the capacity of repeating a given experiment. However, they are aimed at single machine setups, they do not consider distributed environments and different environments that could interact between them.

Methods for setting up the environment of experimentation

Manual The experimenter deploys a golden image that will be provisioned manually. The image modifications have to be saved some way (e.g snapshots) and several versions of the environment can be created with testing purposes. Possibly, the experimenter has to deal with the contextualization of the images or it could be done using the underlying testbed infrastructure. In terms of reproducibility, the experimenter end up with a set of pre-configured software appliances that can be deployed later on the platform by him/her or another experimenter. This approach is relevant due to its simplicity and has been used and mentioned in [START_REF] Dudley | In silico research in the era of cloud computing[END_REF] and [START_REF] Brammer | Paper mch: Creating dynamic reproducible science[END_REF]. Despite its simplicity, the storing of software appliances or snapshots incurs in high storage costs.

Script Automation It is as well based on the deployment of golden images, however, the provisioning part is automated using scripts. The experimenter possibly has no need to save the image, because it can be reconstructed from the golden image at each deployment. Many experimenters opt for this approach because it gives a certain degree of reproduciblity and automation and it is simple compared to using configuration management tools. This was used in [START_REF] Balouek | Flauncher and DVMS -Deploying and Scheduling Thousands of Virtual Machines on Hundreds of Nodes Distributed Geographically[END_REF] for deploying and scheduling thousands of virtual machines on Grid'5000 testbed. Script automation incurs in less overhead when the environment has to be transmitted, for post execution. Nevertheless, it is still dependent on the images provided by the underlying platform.

Configuration management tools Unlike the previous approaches, the golden images are provisioned this time with the help of configuration management tools (e.g., Chef2 or Puppet3 ) which gives to the experimenter a high degree of automation and reproducibility. However, the process of porting the non-existing software towards those tools is complex and some administration expertise is needed. In [START_REF] Klinginsmith | Towards reproducible escience in the cloud[END_REF] it is shown the viability of reproducible eScience on the cloud through the use of configuration management tools. A similar approach is shown in [START_REF] Bresnahan | Managing appliance launches in infrastructure clouds[END_REF].

Software appliances Experimenters can opt for software appliances that have to be contextualized at deployment time. In [START_REF] Keahey | Contextualization: Providing one-click virtual clusters[END_REF] the viability of this approach was shown. Those images can be either built or downloaded from existing testbed infrastructures (e.g Grid'5000, FutureGrid) or sites as TURNKEY 4 or Cloud market5 oriented to Amazon EC2 images. Those images are independent from the ones provided by the platform and experimenters have access to more operating system flavors. The process of image building relies on widely available tools that will be analyzed in the next subsection.

Software appliances builders

We use the term software appliance, which is defined as a pre-built software that is combined with just enough operating system (jeOS) and can run on bare metal (real hardware) or inside a hypervisor. A virtual appliance is a type of software appliance, which is packed in a format that targets a specific platform (normally virtualization platform). A software appliance encompasses three layers:

-Operating System: In the broadest sense includes the most popular operating systems (e.g GNU/Linux, Windows, FreeBSD). This element of the appliance can also contain modifications and special configurations, for instance a modified kernel. -Platform Software: This encompasses compiled languages such as C, C++ and interpreted languages such as Python and Ruby. Additionally, applications or middle-ware (e.g., MPI, MySQL, Hadoop, Apache, etc). All Those software components are already configured. -Application Software: New software or modifications to be tested and studied.

Vagrant6 and Veewee7 are complementary tools to create and configure lightweight, reproducible, and portable development environments. Veewee automatically builds virtual machine images of different Linux distributions. Those images can be exported as so called Boxes that are run on top of the most popular virtualization technologies (e.g., VirtualBox, VMware, etc.). Vagrant provision these Boxes using industry-standard configuration management tools such as shell scripts, Chef or Puppet that will automatically install and configure software. The idea of Vagrant is the creation of disposable and consistent environments that can be re-built from scratch. BoxGrinder8 creates appliances from simple plain text descriptions for various platforms. Unlike previous tools, it uses the host system to perform the image creation which results in a faster process. Those tools are widely used in Cloud infrastructures for generating customized virtual appliances. In theory any experimenter could reconstruct the virtual appliances using the same tool and the same specifications provided by other experimenter. However, the main hurdle is the dependency on external repositories, for instance, 30% of Veewee definitions files point to repositories that not longer exist or some packages are missing for a complete installation.

Reproducible software appliances

We extended our previous work Kameleon [START_REF] Emeras | Reconstructing the software environment of an experiment with kameleon[END_REF] which is a very simple software appliance generator that enables the construction and exact post reconstruction of a given software appliance from text descriptions. It is targeted to make easier the reconstruction of custom software stacks in HPC, Grid, or Cloudlike environments. Kameleon takes care of the following steps in the process of software appliance generation:

-Operating system: Construction of the respective O.S file system layout, which encompasses the necessary binaries, libraries, configuration files in order to run. This depends on the distribution chosen for the software appliance. -Provision: Installation of different software packages required for the appliance. This can be done through the package manager of the distribution chosen, from source tarballs, or using configuration management tools. -User's code: This step will add user's modifications or applications that the user wants to experiment with. -Save output: Save the generated image into a particular format: Virtual machine format, LiveCD, raw disk image, etc.

Kameleon approach is based on two contexts, namely execution context which is where Kameleon engine is executed (e.g., user's machine) and construction context in charge of generating the file system layout of the appliance. Kameleon can use different operating system-level virtualization techniques such as: chroot (the less isolated but the lightness one) or Linux Containers as well as full virtualization (e.g., VirtualBox, kvm) and real machine (the most isolated but the heaviest one). Each context has its own advantages and disadvantages. As exposed before, using the user's machine to build the appliance could result in a faster build process. Kameleon enables to take advantage of the most convenient approach given the user's requirements. The process of construction or reconstruction has to take care of some possible issues caused by, for example, isolation and portability. Special needs can be specified in Kameleon metadata.

Our previous work was extended mainly in two points: (1) Requirements for a reproducible software appliance were identified, (2) The implementation of a persistent cache mechanisim. Both points will be described next.

Requirements for a reproducible reconstruction

The approach for software appliance construction and reconstruction is based on four requirements:

1. A recipe (Fig 1) that describes how the software appliance is going to be built. This recipe is a higher level description easy to understand and contains some necessary meta-data in form of global variables and steps. For more details [START_REF] Emeras | Reconstructing the software environment of an experiment with kameleon[END_REF] global -exec_appliance: cp $$stepdir/data/oar_mysql_db_init $$chroot/usr/lib/oar/ -exec_chroot: oar_mysql_db_init -update_hostfile:

-append_file:

-/etc/hosts -| 127.0.0.1 node1 node2 -create_resources:

-exec_chroot: oarnodesetting -a -h node1 2. The DATA which is used as input of all the procedures described in the recipe. It encompasses software packages, tarballs, configuration files, control version repositores, scripts and every input data that make up a software appliance. Whenever used the term DATA in this paper, it will refer to this. 3. Kameleon engine consist in 700 lines of ruby code which parses the recipe and carry out the building. This part includes as well the persistent cache mechanism that will be described later on. This is the user interface to Kameleon. 4. Metadata that describes the compatibility and requirements between execution context and construction context.

Therefore, the problem of guaranteeing the exact reconstruction of software appliances is reduced to keeping the parts of Kameleon unchanged: (1) the recipe, (2) DATA (3) Kameleon engine. Two different experimenters having those three exact elements and fulfilling the requirements of context interactions (4) will generate the same software appliance. Kameleon can generate in an automatic and transparent way a cache file that will contain the exact DATA used during the process of construction along with the recipe, steps and metadata, all bundled together enabling the easy distribution. The low size of Kameleon engine and Polipo (less than 1MB) makes feasible the distribution of the exact versions used to create the environment, avoiding the incompatibility between versions. The whole process is depicted in Fig 2 . More information can be found in [START_REF] Emeras | Reconstructing the software environment of an experiment with kameleon[END_REF] or in Kameleon web site9 .

Persistent cache mechanism

Our approach to achieve replicability is to use a persistent cache to capture all the DATA used during the construction. As we cannot guarantee that a Fig. 2: Software appliance creation with Kameleon particular download link will exist forever or always point to the same software with the same version. A persistent cache mechanism brings the two followings advantages: (a) Data can always be retrieved and (b) The software versions will be exactly the same.

Design

The caching mechanism has to be transparent and lightweight for the user in the two phases of the Kameleon approach: the construction of the software appliance, and its respective ulterior reconstruction. As most of DATA comes from the network (e.g., operating system, software the obvious approach was to integrate a caching proxy for web. Such a caching proxy will capture transparently every piece of data downloaded using the network. However, there are still some parts of the DATA missing, because some files -that make the software appliance unique -are provided by the user from its local machine or even worse some packages cannot be cached. That is the reason why we opted for an approach consisting in two parts:

-A caching web proxy, that caches packages coming from the network. This relies on Polipo10 which is a very small, portable and lightweight caching web proxy. We chose Polipo because it can run with almost zero configuration. -Ad hoc procedures that cache what could not be cached using the caching web proxy (e.g., version control repositores, https traffic) and all data from the local machine. These Ad hoc procedures are based on simple actions depending on the data to cache. Modifications on the fly of the steps involved on those Ah doc procedures are necessary.

In order to make more clear the composition and limitations of the persistent cache, we define four properties of DATA:

-Location: it can be either Internal (I) or External (E).

-Cacheability: whether it is possible to cache it (C) or not ( C).

-Method of caching: it can be Proxy (P) or Ad hoc (A). -E,C,P: data which comes from an external location (e.g., local network, internet) and can be cached with the proxy (e.g., Software packages, tarballs, input data). -E,C,A: same external location, however, it cannot be cached with the proxy (e.g., version control repositories, https traffic). -E, C: this data comes from an external location but can not be cached due to some restrictions (e.g., proprietary licenses) or due to its size it can not be stored (e.g., big databases). -I,C,A: data that comes from the local machine and it is cached by some ad hoc procedures. -I, C: it comes form local machine but can not be cached. In order to show that our approach is very portable between versions of Linux distributions. We carried out successfully construction and reconstruction of different appliances as shown in Table 1 that consist in different flavors of GNU/Linux (Debian, Ubuntu) and middleware: OAR [START_REF] Capit | A batch scheduler with high level components[END_REF] a very lightweight batch scheduler, Hadoop11 and TAU 12 . It was possible to reproduce old environments of test back to 2009. A design goal was to achieve a self contained cache. Hence, we tested the portability of the persistent cache mechanism. The aforementioned software appliances where reconstructed using their respective persistent cache files, the Kameleon engine and the Polipo binary which made only 984 K Bytes. This was tested in the following Linux distributions: Fedora 15, OpenSUSE 11.04, Ubuntu 10.4 and CentOS 6.0.

Experimental results and validation

Building old environments

The persistent cache mechanism enable the building of environments generated at any point of time. It does so by using the same versions that are compatible with the scripts used at the moment of the first generation of the software appliance. Not using the same exact versions can sometimes generate unexpected errors that are time consuming and researchers do not want to deal with.

We faced those problems when building software appliances based on Archlinux distribution and on the OAR batch scheduler. Their current versions posed several incompatibility problems with the scripts used for generating the software appliances a year ago. The persistent cache mechanism enabled the reconstruction of these software appliances. All the examples presented in this paper can be reproduced accesing the Kameleon site 13 .

Conclusions and Future Works

Experiment reproduciblity is a big challenge nowadays in computer science, a lot of tools have been proposed to address this problem, however there are still some environments and experiments that are difficult to tackle. Commonly, experimenters lack of expertise to setup complex environments necessary to reproduce a given experiment or to reuse the results obtained by someone else. We presented in this paper, a very lightweight approach that leverage existing software and allows an experimenter to reconstruct independently the same software environment used by another experimenter. Its design offers a low storage requirement and a total control on the environment creation which in turn allows the experimenter to understand the software environment and introduce modifications into the process. Furthermore, several methods to carry out the setup of the environment for experimentation were described and we show the advantages of our approach Kameleon. As a future work we plan to carry out more complex experiments with our approach and measure the gains in terms of reproducilibity and complexity as well as to study the contextualization of environments (e.g., post installation process) in different platforms.

Acknowledgments

Experiments presented in this paper were carried out using the Grid'5000 experimental testbed, being developed under the INRIA ALADDIN development action with support from CNRS, RENATER and several Universities as well as other funding bodies (see https://www.grid5000.fr).

Fig. 1 :

 1 Fig. 1: Recipe and step example

  -Scope: two possible values Private or Public. The scope makes necessary the creation of two types of cache Private and Public for distribution purposes. Combining the properties Location, Cacheability and Method of caching we can identify five types of data:

Table 1 :

 1 Software appliances generated

	General Appliances
	Name	Main software stack Size [MB]		OAR Appliances
		Java 1.6		OAR Version date of release GNU/Linux version Size [MB]
	Hadoop	Hadoop 1.03	229	2.2.17	27 Nov 2009	Debian etch	112
		Ubuntu 10.04 LTS		2.3.5	30 Nov 2009	Debian etch	113
		PAPI 5.1.0		2.4.7	11 Jan 2011	Debian Lenny	137
	HPC Profiling	TAU 2.22 OpenMPI 1.6.4	226	2.5.0 2.5.2	5 Dec 2011 23 May 2012	Debian Squeeze Debian Squeeze	140 140
		Debian Wheezy

http://www.opscode.com/chef/

https://puppetlabs.com/

http://www.turnkeylinux.org

http://thecloudmarket.com/

http://www.vagrantup.com/

https://github.com/jedi4ever/veewee

http://boxgrinder.org/

kameleon.imag.fr

http://www.pps.jussieu.fr/ jch/software/polipo/

http://hadoop.apache.org/

http://www.cs.uoregon.edu/research/tau/home.php

http://kameleon.imag.fr/


Mathieu Bertin

Edith C Fayolle

Claire Romanzin

Hugo A M Poderoso

Xavier Michaut

Laurent Philippe

Pascal Jeseck

Karin I Öberg

Harold Linnartz

Jean-Hugues Fillion

Indirect ultraviolet photodesorption from CO:N 2 binary ices -an efficient grain-gas process

Keywords: Astrochemistry -ISM, abundances -ISM, molecules -Molecular processes

UV ice photodesorption is an important non-thermal desorption pathway in many interstellar environments that has been invoked to explain observations of cold molecules in disks, clouds and cloud cores. Systematic laboratory studies of the photodesorption rates, between 7 and 14 eV, from CO:N 2 binary ices, have been performed at the DESIRS vacuum UV beamline of the synchrotron facility SOLEIL. The photodesorption spectral analysis demonstrates that the photodesorption process is indirect, i.e. the desorption is induced by a photon absorption in sub-surface molecular layers, while only surface molecules are actually desorbing. The photodesorption spectra of CO and N 2 in binary ices therefore depend on the absorption spectra of the dominant species in the subsurface ice layer, which implies that the photodesorption efficiency and energy dependence are dramatically different for mixed and layered ices compared to pure ices. In particular, a thin (1-2 ML) N 2 ice layer on top of CO will effectively quench CO photodesorption, while enhancing N 2 photodesorption by a factors of a few (compared to the pure ices) when the ice is exposed to a typical dark cloud UV field, which may help to explain the different distributions of CO and N 2 H + in molecular cloud cores. This indirect photodesorption mechanism may also explain observations of small amounts of complex organics in cold interstellar environments.

Introduction

In cold and dense regions of the interstellar medium (ISM), characteristic of star and planet formation, gaseous atoms and molecules stick onto dust grains forming ice mantles in relatively short time scales. At these very low temperatures (< 20 K), thermal desorption is negligible for all molecules except H 2 . Yet, molecules are detected in the gas phase for temperatures below their condensation temperature and this implies the existence of efficient non-thermal desorption processes. These comprise desorption induced by cosmic rays, chemically-induced desorption and vacuum UV photodesorption. The latter has been proposed as an important desorption pathway, particularly in the surface layers of protoplanetary disks (Dominik et al. 2005;Hogerheidje et al. 2011;Willacy & Langer 2000). It may also account for the gas-to-ice abundance ratio for a number of species as observed in other dense regions of the ISM (Coutens et al. 2012;Hollenbach et al. 2009), including the edges of molecular clouds where external UV photons can alter the ice mantle formation, or in the inner part of dense molecular clouds where UV photons are produced by the cosmic-ray ionization of H 2 (Caselli et al. 2012). Photodesorption, therefore, is of general importance, influencing the chemistry at different locations in denser regions in space.

Quantitative photodesorption yields from low temperature ices were first obtained experimentally for H 2 O (Westley et al. 1995a,b). Over the last five to seven years photodesorption rates have been determined for other pure ice samples using broad band, hydrogen discharge lamps: CO (Muñoz Caro et al. 2011;Oberg et al. 2007), H 2 O/D 2 O (Oberg et al. 2009a), N 2 and CO 2 (Bahr & Baragiola 2012;Oberg et al. 2009b;Yuan & Yates 2013), O 2 and O 3 (Zhen & Linnartz 2013). Molecular dynamics calculations have been performed for water ice (Andersson et al. 2005(Andersson et al. , 2006;;Arasa et al. 2011) and are in good agreement with the experimental findings. More recently, wavelength-specific studies have been performed and for CO, N 2 and O 2 absolute photodesorption rates have been determined between 7 and 14 eV (Fayolle et al. 2011(Fayolle et al. , 2013)). The spectral dependence of the photodesorption yield is of fundamental interest for modeling regions in space with different spectral energy distributions. Moreover, this approach has been very successful to link the photodesorption process in the ice to the solid state mechanisms at play, highlighting the physical-chemical parameters governing the photodesorption process. In the case of CO and N 2 the wavelength dependent intensity of the measured Photon-Stimulated Desorption signals (PSD) follows directly the electronic transitions in the condensed molecules (Fayolle et al. 2011(Fayolle et al. , 2013)). This is a signature of a mechanism known as DIET (desorption induced by electronic transition), not (substantially) involving dissociation/recombination in the ices. An even more detailed picture of the involved surface processes has been derived from the investigation of layered 13 CO/ 12 CO films (Bertin et al. 2012) showing that the photodesorption is mediated by the ice lattice. This study pointed out a sub-surface excitation mechanism in which electronically excited molecules release their energy through intermolecular vibrational motion into a desorption channel. Recently, Yuan & Yates (2013) addressed the crucial role of this energy transfer from the ice lattice by comparing Lyman-α photodesorption at 75 K for pure 12 CO 2 , pure 13 CO 2 and 12/13 CO 2 mixed ices.

In the present work we go one step further and study the photodesorption efficiency of a binary ice mixture made of different chemical species. We present wavelength dependent photodesorption measurements from CO and N 2 binary ices (layered and mixed) at 10 K. This is interesting from a physical-chemical point of view; their masses are nearly equivalent, their photodesorption mechanisms are similar and their binding energies to the solid are comparable, but the two molecules have strong, non-coinciding photodesorption features in the VUV (around 8.5 and above 12.3 eV for CO and N 2 , respectively) in their pure solid phase. The choice for a CO:N 2 ice is particularly relevant from an astronomical point of view. CO is highly abundant, both in the gas phase and in the solid state, representing the main molecular component after H 2 . Molecular nitrogen, N 2 , is not directly detectable due to its lack of a permanent dipole moment, but is considered as one of the main reservoir of nitrogen in the gas phase, due to its high stability. Its presence in the ISM is evidenced by the detection of N 2 H + resulting from a proton transfer reaction involving H + 3 (Bergin et al. 2002;Flower et al. 2006;Hily-Blant et al. 2010). Moreover, N 2 stands at the origin of other processes leading to the formation of more complex N-bearing molecules (Hily-Blant et al. 2013;Persson et al. 2010Persson et al. , 2012)). As both CO and N 2 are highly volatile, with accretion temperatures in the 16-20 K regime under ISM conditions and sticking coefficients close to unity, they are the last species to freeze onto dust grains, generating a top layer that can be considered as a binary interstellar ice (Bisschop et al. 2006;Oberg et al. 2005).

In this letter we present a laboratory based study of vacuum UV irradiated CO:N 2 binary ice samples as a function of the wavelength. This approach follows successful experiments on pure CO, N 2 and O 2 ice (Fayolle et al. 2011(Fayolle et al. , 2013;;Bertin et al. 2012). In the next section experimental details are given. The results are presented in section 3 and are discussed from a physical-chemical and an astrophysical point of view in section 4.

Experimental methods

The photodesorption studies are realized in the SPICES (Surface Processes & ICES) setup of the UPMC (Université Pierre et Marie Curie), under ultrahigh vacuum (UHV) conditions (P ∼ 1×10 -10 Torr). The substrate on which ices are grown is a Highly Oriented Polycrystalline Graphite (HOPG) surface. It is mounted on the tip of a turnable coldhead that can be cooled down to ∼ 10 K by means of a closed cycle helium cryostat. The ice layers are grown in-situ by exposing the cold HOPG substrate to a partial pressure of CO and/or N 2 gases. A dosing tube, placed 1 mm in front of the substrate, allows a local exposure of the gases onto the cold sample without contaminating the whole UHV chamber. The isotopologues 13 CO (Eurisotop, 99.6 % 13 C) and 15 N 2 (Eurisotop, 97 % 15 N) are used in order for them to be distinguishable by mass spectrometry. The quantities of molecules deposited on the substrate are expressed in ML eq (monolayer equivalent) corresponding to the surface density of a compact molecular layer on a flat surface, with 1 ML eq ≈ 1×10 15 molecule.cm -2 . Temperature Programmed Desorption (TPD) is used for the calibration of the ice thicknesses, resulting in reproducible parameters for the growth conditions with a precision better than 1 ML eq . UV photodesorption is induced through irradiation of the ice sample by the continuous output of the undulator-based vacuum UV DESIRS beamline of the synchrotron SOLEIL (Nahon et al. 2012), providing photons with an energy that can be continuously scanned over the 7 -14 eV range. A narrow bandwidth of typically 40 meV is selected by the 6.65 m normal incidence monochromator that is implemented on the beamline. A gas filter in the beamline suppresses the harmonics of the undulator that can be transmitted in higher diffraction orders of the grating. The absolute incident photon flux per surface unit impinging onto the sample is measured by a calibrated photodiode and varies for a given spectral bandwidth of 40 meV between 0.3 and 1.1×10 13 photons.s -1 .cm -2 depending on the photon energy. In order to prevent radiation cut-off, the DESIRS beamline is directly connected to SPICES, i.e., without any window.

The photon-stimulated desorption (PSD) spectra are obtained as follows: the signals of desorbing species with given masses are recorded as a function of time using a Quadrupole Mass Spectrometer (QMS), while the sample is irradiated with photons whose energy is continuously scanned from 7 to 14 eV with steps of 25 meV. This gives the mass signal of desorbing species as a function of the incident photon energy, which can be converted into an absolute photodesorption yield, in desorbed molecule per incident photon, using (i ) the measured energy-dependent photon flux and (ii ) the calibration of the mass signal into absolute amount of desorbed molecules. More details on this calibration step have been previously given in Fayolle et al. (2011) and Fayolle et al. (2013). It is important to note that this treatment does not significantly change the global shape of the PSD spectra: the observed structures in calibrated PSD spectra are already clearly visible in the unprocessed signals.

Each energy step lasts ∼ 5 s. In parallel, the QMS signal is recorded with a dwell of 1 s, which makes an average of 5 points per energy step. Caution has been taken to ensure that for each data point the 1 s accumulation time is substantially longer than the QMS mass signal build-up time, preventing eventual artefacts due to fast wavelength scanning. Each PSD spectra from 7 to 14 eV is made continuously on the same sample. An energy scan from 7 to 14 eV lasts 23 minutes. From our calibrated PSD spectra and the evolution of the photon flux with time and energy, we can estimate the total amount of desorbed molecules per scan for each PSD spectrum. At the maximum, we find a total density of photodesorbed molecules of ∼10 13 molecule.cm -2 , which corresponds to 10 -2 ML eq . Therefore, the amount of photodesorbed molecules during one single scan is negligible compared to the total amount of molecules available in the ice, which at its lowest value amounts to 0.9 ML eq . The photoprocessing of the ice is not expected to modify the photodesorption rate from the beginning to the end of the scan. This is confirmed experimentally, since PSD spectra obtained two times in a row on the same sample are identical.

In order to make a clear separation between signals associated with 13 CO (m = 29 amu) and 15 N 2 (m = 30 amu), we verified that our QMS mass resolution is sufficient to differentiate each mass peak. From the mass spectra of the pure products and the mixture of both we derive a resolution of ∼ 0.3 amu, as taken from the Full-Width-at-Half-Maximum (FWHM) of the Gaussian mass peaks. It is accurate enough to allow for a fine separation of 13 CO and 15 N 2 signals that have indeed a negligible overlap, as can be clearly seen in the corresponding mass spectra, available in appendix A.

Results

Figure 1a shows PSD spectra obtained upon VUV irradiation of the pure 13 CO and 15 N 2 ices. These spectra have already been presented and discussed in previous studies. The photodesorption rates exhibit energy-dependent efficiencies that follow closely the VUV absorption of the pure molecular solids, with patterns that are associated with electronic transitions of the condensed molecules. For instance, the features observed between 7.9 and 9.5 eV in the CO PSD spectrum are due to vibronic bands in the A 1 Π-X 1 Σ + (v',0) electronic transition, each peak being associated with a transition towards a vibrational sub-level v' in the A-state of solid 13 CO (Fayolle et al. 2011). In a similar way, the main feature responsible for the photodesorption of solid 15 N 2 (above 12.3 eV) is associated with the b 1 Π u -X 1 Σ + g (v',0) transition in pure nitrogen ice (Fayolle et al. 2013). The observation of such structures in the energy-resolved photodesorption rates is a clear signature for a DIET mechanism, as discussed in Fayolle et al. (2011Fayolle et al. ( , 2013)). It has been shown that the excitation mainly takes place in a subsurface region of the ice (2-3 upper molecular layers), while only the molecules from the topmost layer are ejected into the gas phase. A short-range energy transfer from the excited to the desorbing molecules is therefore expected to occur, presumably through the coupling between the relaxation of the excited species and the excitation of intermolecular collective vibrational modes (Bertin et al. 2012). It should be noted that the thickness of our samples is less than the photon penetration depth, implying that photons can excite molecules deeper within the ice and even reach the graphite substrate. However, according to Bertin et al. (2012), neither the substrate nor underlying layers are contributing to the desorption features observed here. The question that is addressed here is how these properties translate in a mixed ice, consisting of both CO and N 2 .

3.1. Photodesorption from mixed CO:N 2 ice Figure 1b displays the PSD spectra for both 13 CO and 15 N 2 desorbing upon VUV irradiation of an ice grown from a 1:1 CO:N 2 mixture. There is a clear difference between the results for the pure and mixed ice irradiation. As discussed above, the pure ice spectra are very different, whereas, for the mixed ice, the PSD spectra are identical. A comparison with Fig. 1a shows that the photodesorption spectra of the CO:N 2 ice mixture results in a superposition of the PSD spectra of the two pure constituents. The ejection of any surface molecule in the mixed ice, clearly, is initiated by the electronic excitation of any other molecule. In particular, the PSD spectra of the mixed ice show that the excitation of solid CO into its A 1 Π state leads to the desorption of surface N 2 (7.9 -9.5 eV), and that solid N 2 excitation into its b 1 Π u state initiates CO desorption above 12.3 eV. This finding is fully consistent with the previously introduced concept of an indirect DIET mechanism; part of the excess energy deposited in the ice by the vacuum UV photon absorption is transferred from one to the other molecule independently of its chemical nature -causing desorption.

For a given energy, the absolute photodesorption rates of CO and N 2 from the mixed ice are lower by a factor of 2 than the corresponding value derived for the pure ices. In fact, the PSD spectra of the mixture can be fitted with a very good agreement by a linear combination of the desorption spectra of pure 15 N 2 and pure 13 CO in which each constituent contributes to about ∼ 0.5 of the overall desorption signal (Fig. 2). As the surface of the mixed film is expected to be composed of half CO and half N 2 molecules, and as the adsorption energies of CO and N 2 are very close (Bisschop et al. 2006), this shows that the amount and efficiency of the energy transfer to surface molecules upon subsurface CO excitation or N 2 excitation are about the same.

3.2. Photodesorption from layered N 2 /CO and CO/N 2 ices Photon-stimulated desorption spectra of 13 CO (left panel) and 15 N 2 (right panel) obtained from a pure 25 ML eq 13 CO ice covered by an increasing layer of 15 N 2 are shown in Fig. 3. In the case of pure CO or N 2 ice (top left and bottom right, respectively) the characteristic desorption profiles around 8.5 and above 12.3 eV are seen. When the CO ice is covered by 0.9 ML eq of N 2 , the CO desorption yield drops substantially, and it is almost entirely suppressed above ML eq . This behavior, also observed in the case of layered 13 CO/ 12 CO (Bertin et al. 2012), shows that mostly the surface molecules are susceptible to desorb upon UV irradiation.

When investigating the PSD of 15 N 2 for a low thickness of N 2 overlayer (0.9 ML eq ), one can see that its photodesorption pattern mimicks almost completely the one of the pure CO ice, demonstrating that its photodesorption is triggered only by the absorption of the underlying CO molecules. In particular, its photodesorption in the 7.9 -9.5 eV range, associated with the excitation of the A 1 Π state of solid CO, becomes the dominant contribution, although pure solid N 2 does not photodesorb at these energies. In contrast, photodesorption initiated by the N 2 excitation in the b 1 Π u state (> 12.3 eV) is not clearly observed. This cannot be explained by the lack of surface N 2 at the end of the energy scan, since less than 0.01 ML eq of N 2 has been ejected into the gas phase during the acquisition time. The adsorption of a small quantity of N 2 onto a CO ice therefore drastically modifies the energy-dependence of its photodesorption process. For increasing thickness of the 15 N 2 overlayer, the N 2 excitation contribution to the N 2 PSD spectra gradually recovers the one of the pure N 2 ice. The contribution of the CO excitation becomes very weak for N 2 thicknesses above ML eq , showing that the range for an efficient energy transfer involves less than 3 molecular layers.

Figure 4 shows the results of layered experiments in which 25 ML eq 15 N 2 ice is covered by an increasing layer of 13 CO. The experiment is essentially identical to the previous one (fig. 3), but the role of N 2 and CO are exchanged. The N 2 photodesorption signal vanishes for a larger CO coverage and a clear vibrational progression in the 13 CO desorption channel is found that corresponds to an excitation into the b 1 Π u state of N 2 . This feature is superimposed over a continuous desorption of 13 CO observed above 12.5 eV in pure CO samples (Fayolle, et al. 2011). As for the 25 ML eq 13 CO ice covered by 15 N 2 the spectra are fully consistent with a process in which only surface molecules desorb after excitation of sub-surface species.

Discussions and astrophysical implications

Role of ice structure and composition on absolute photodesorption rates

The VUV photodesorption of coadsorbed N 2 and CO presents very different energydependent profiles and efficiencies compared to pure N 2 and CO ices. Both molecules mainly desorb through an indirect mechanism, where the excitation of a subsurface molecule, whether CO or N 2 , leads to the desorption of N 2 and CO surface molecules. Because this indirect mechanism involves energy transfer from the excited molecule to the desorbing one, presumably by collective vibrational mode excitation, the photodesorption energy-dependence and efficiency depend strongly on the nature of the intermolecular interactions. In general intermolecular interactions in solids may promote the photodesorption, but also quench it. This has been demonstrated for CO 2 in interaction with other isotopologues or rare gas matrices (Yuan & Yates 2013), and for CO in interaction with H 2 O ice (Bertin et al. 2012). For the latter case, an explanation has been proposed, stating that the photodesorption efficiency is driven by the competition between two excess energy relaxation pathways: (i ) relaxation by intermolecular phonon modes of the ice, coupled to desorption and (ii ) relaxation by transfer to intramolecular vibration modes of neighboring molecules. If the first relaxation pathway is dominant, the photodesorption will be efficiently triggered by UV absorption of neighboring molecule. If the latter pathway dominates the relaxation process, as it is the case when excited CO transfers efficiently its excess energy to the O-H dangling bond vibrations of neighboring water molecules, then the photodesorption gets hindered. In both cases, the constructive and destructive matrix effects are a consequence of the indirect character of the photodesorption mechanism.

Because the intermolecular coupling in the ice between excited and surface molecules can drastically modify the photodesorption process, it is expected that different composition, but also different structure of the ice, will modify the energy-integrated photodesorption yield for a given UV field. This is illustrated for the N 2 /CO binary ices. As shown in Figs. 1 and3, coadsorption of N 2 with CO promotes N 2 desorption in the 7 -11.5 eV range whereas it decreases the desorption efficiency of CO in the same energy range. To quantify this effect, energy-integrated photodesorption rates have been derived from our PSD curves for three types of interstellar vacuum UV profiles as a function of the CO:N 2 layered/mixed ices composition. The results are displayed in Table 1. To obtain these values, our energyresolved desorption rates have been convoluted with vacuum UV profiles describing the interstellar radiation field (ISRF) at the edge of clouds (Mathis et al. 1983), the effect of secondary photons from cosmic ray impacts in dense cores (Gredel et al. 1987), and a TW Hydrae radiation field as model for the UV field in proto-planetary disks (Herczeg et al. 2002;Valenti et al. 2003;Johns-Skrull & Herczeg 2007). The resulting photodesorption rates are varying depending on (i ) the UV field considered, (ii ) the ice composition and (iii ) the internal ice organization (layered versus mixed). Compared to pure ices the photodesorption rates from the binary ices change by up to an order of magnitude. The general trend is to decrease the CO photodesorption rate from > 1 ×10 -2 to 2-6 ×10 -3 molecules.photon -1 , and to increase the N 2 photodesorption rate by a factor of 2-3. This shows that a proper description of the VUV photodesorption process has to take into consideration the structure and composition of the ice on which the molecules are adsorbed; the photodesorption rates extracted from pure molecular solids may not be realistic in the case of more complex ices, as typically present in the insterstellar medium.

Implications for N 2 and CO gas phase abundance in dense cores

In dense cores, N 2 and CO are expected to freeze out onto dust grains at very low temperatures, less than 2 K apart, and with the same sticking efficiency (Bisschop et al. 2006;Oberg et al. 2007). Consequently, a similar depletion in the gas phase should be observed. Nevertheless, observational studies of N 2 H + and other N-containing species in dense cores providing data to indirectly derive the N 2 abundance suggest that N 2 depletion on grains occurs later, i.e. at a higher density, than for CO (Bergin et al. 2002;Pagani et al. 2005Pagani et al. , 2012)). Therefore, it has been suggested that another mechanism is repsonsible for a continuous enrichment of gas phase N 2 , counterbalancing its accretion onto grains. Chemistry involving CN + N reactions, constantly forming N 2 in the gas, is invoked (Hily-Blant et al. 2010). Nonthermal desorption processes, such as photodesorption, could also contribute to this effect by preferentially ejecting N 2 instead of CO in the gas phase. Nevertheless, the photodesorption rates as extracted from pure CO and N 2 ices cannot resolve this issue since for realistic dark cloud UV field the photodesorption rate is substantially lower for pure N 2 than for pure CO ice (Table 1). However, considering pure ices only may be inappropriate, as discussed in section 4.1, since ice structure and composition influence the CO and N 2 photodesorption rates.

Since CO and N 2 are expected to freeze-out in the same temperature range, it is rather unlikely that the top layers of the ices are composed solely of pure N 2 or pure CO thick layers. Instead, we expect that both species are coadsorbed at the surface of the icy grains. The exact nature of the top layers depends on the total abundance of N 2 as compared to CO, as well as on the proximity in time and space of CO and N 2 freeze-out. The amount of gas phase N 2 being relatively low compared to CO (Bergin et al. 2002;Maret et al. 2006), it is expected that solid phase N 2 will be embedded in a CO-rich environment. Whether the outer layers of the grain will be layered or mixed is not that easy to answer, and is likely source-dependent. N 2 is expected to condense for a temparture that is 2 K lower than for CO (Flower et al. 2006;Hily-Blant et al. 2010), which would, for low cooling speed of the cloud, lead to the growth of a thin N 2 layer on top of CO-rich ice. In the case of a shorter cooling time, such a temperature difference would not be sufficient to result in segregated layers, and N 2 would be intimately mixed with the CO.

Table 1 shows that for realistic dark cloud UV field photodesorption rates extracted from pure N 2 ice is substantially lower for than for pure CO ice. If we consider instead mixed CO:N 2 1:1 ice, the photodesorption rates of CO and N 2 in prestellar cores are identical. In the case of a more realistic system, i.e. a small amount (0.9 ML eq ) of N 2 on CO ice, then, the CO photodesorption rate strongly decreases, whereas the N 2 photodesorption rate is promoted. Then, the N 2 desorption becomes more efficient than the CO one, and photodesorption can contribute to gas phase N 2 enrichment. We conclude that under interstellar conditions N 2 will be photodesorbed at least as efficiently as CO as long as they are coadsorbed. In many core environments, the N 2 photodesorption may exceed that of CO providing a natural explanation to why N 2 is maintained longer in the gas phase compared to CO.

Organics desorption through CO photoexcitation?

The indirect nature of the photodesorption process may have general implications beyond the explanation of the CO and N 2 abundances in the ISM. The ability of CO ice to transfer part of the absorbed energy to a surrounding molecule may act as an important indirect photodesorption channel of other species as well. This could be true in particular for chemically linked formaldehyde H 2 CO and methanol CH 3 OH, and possibly even more complex organic molecules, providing a non-dissociative non-thermal desorption pathway. Indeed, such organics are expected to efficiently photodissociate upon UV photon irradiation, as it has been found for CH 3 OH (Oberg et al. 2009c), leading to the formation of photoproducts that can eventually desorb. Embedded in a CO-rich environment, however, such molecules may react differently under UV irradiation: a photon absorption by the surrounding and more numerous CO molecules could lead to the desorption of the surfacelocated organics via a similar mechanism as highlighted for CO:N 2 . Such a process could then explain the observed gas abundances of organics, observed in the cold regions of the ISM (Bacmann et al. 2012;Oberg et al. 2010;Tercero et al. 2013). Whether this indirect photodesorption process can be generalized to heavier and more strongly bound species than CO and N 2 needs to be experimentally verified, however.

Summary and conclusions

From a systematic set of energy (7 -14 eV) resolved (40 meV) photodesorption laboratory studies on CO:N 2 binary ices, both mixed and layered the following conclusions can be made:

• The desorption is induced by a photon absorption in the topmost molecular layers, while only surface molecules are actually desorbing. This implies an energy transfer from the subsurface excited molecule to the surface ones. Thus, the photodesorption rate is not linked to the absorption spectrum of the desorbing molecule, but is instead associated to the absorption profile of the surrounding species, located deeper in the ice. When N 2 and CO are mixed in equal proportions, their photodesorption spectra become superimposable, and reflect a linear combination of the photodesorption spectra of both pure ices. When a small quantity of N 2 is deposited at the surface of a CO ice, then, its photodesorption spectrum reflects mostly the one of pure CO. This is remarkable since, in this case, the N 2 major desorption feature lies in the 7.9 -9.5 eV energy range, in which pure solid N 2 does not absorb.

• This indirect desorption mechanism and its dependence on ice structure and wavelength influence the (overall) desorption efficiency in space. Considering the range of indirect photodesorption processes, we suggest that the photodesorption rates experimentally obtained from pure ices should only be used for molecules which can form pure phases in the ISM ices, exceeding at least two to three molecular toplayers, as it may be the case for CO in some cold regions (Pontoppidan et al. 2008(Pontoppidan et al. , 2003)). Below this thickness, or when molecules are mixed with others, photodesorption rates obtained from a more realistic composite ice should lead to a more accurate description of the non-thermal desorption. Here both chemical composition and molecular organization play a role.

• The results presented here provide a way to replenish nitrogen in the prestellar cores, contributing to the unexplained low depletion rate of N 2 as compared to CO. If the rates derived for pure CO and N 2 are used, CO should desorb with an efficiency that is almost one order of magnitude higher than for N 2 . This is not in agreement with observations concluding that gaseous CO depletes on the grains with a higher rate than N 2 (Pagani et al. 2012). When considering the rates extracted from a more realistic system, most probably a layered N 2 /CO structure with a small amount of N 2 , as presented here, gaseous N 2 will be enriched with respect to CO. A detailed astrochemical modelling is required to quantify the extent of this N 2 enrichment.

• Finally, the mechanism introduced here may act as a more general desorption process in other mixed ices of astrophysical interest. The CO present in CO-rich icy mantles has the potential to transfer photon energy to kinetic energy of surrounding molecules, triggering their photodesorption in an indirect way. The concerned species could be coadsorbed molecules during the freeze-out process, such as unsaturated carbon chains, but also small organics originating from the hydrogenation of CO, such as H 2 CO and CH 3 OH.

We acknowledge SOLEIL for provision of synchrotron radiation facilities under the project 20120834 and we would like to thank Nelson De Oliveira for assistance on the beamline DESIRS. Financial support from the French CNRS national program PCMI (Physique et Chimie du Milieu Interstellaire), the UPMC platform for astrophysics "ASTROLAB", the Dutch program NOVA (Nederlandse Onderzoekschool voor Astronomie), and the Hubert Curien Partnership Van Gogh (25055YK) are gratefully acknowledged. The Leiden group acknowledges NWO support through a VICI grant. -Photon-stimulated spectra of 15 N 2 and 13 CO from a mixed 13 CO: 15 N 2 30 ML eq ice, in proportion 1:1, compared with a linear combination of PSD spectra obtained from pure 13 CO ice (× 0.5) and pure 15 N 2 ice (× 0.5). The spectra have been acquired from ices deposited on HOPG kept at 15 K. . Table 1: Energy-integrated photodesorption rates of CO and N 2 in several regions of the ISM for pure ices, mixed CO:N 2 ices in a proportion of 1:1, and 0.9 monolayer equivalent (ML eq ) of N 2 deposited on top of a CO ice. The rates are for ices kept at 15 K. All values are given in desorbed molecules per incident photon.

Pure Pure CO from N 2 from Environment CO ice d N 2 ice e Mixture 0.9 ML eq Mixture 0.9 ML eq CO:N 2 1:1 N 2 on CO CO:N 2 1:1 N 2 on CO Edges of clouds a 1.3 × 10 -2 2.6 × 10 -3 5.7 × 10 -3 5.3 × 10 -3 5.5 × 10 -3 8.0 × 10 -3 Prestellar cores b 1.0 × 10 -2 2.2 × 10 -3 3.0 × 10 -3 3.9 × 10 -3 3.0 × 10 -3 5.1 × 10 -3 Protoplanetary disk c 7.2 × 10 -2 5.3 × 10 -3 2.3 × 10 -3 3.0 × 10 -3 2.1 × 10 -3 2.7 × 10 -3

Note. -Using UV field from a Mathis et al. 1983, b Gredel et al. 1987, c Herczeg et al. 2002, Valenti et al. 2003, Johns-Skrull & Herczeg 2007. d and e are values from Fayolle et al. 2011 andFayolle et al. 2013, respectively. .

Fig. 1 .

 1 Fig.1.-Photon-stimulated desorption spectra of 13 CO (red) and 15 N 2 (blue) from 30 ML eq of pure 13 CO and 15 N 2 ices (a), and from a mixed 13 CO: 15 N 2 ice, in proportion 1:1 (b). The electronic transitions in condensed CO and N 2 associated with the main photodesorption features are indicated. All spectra have been obtained for ices kept at 15 K and deposited on HOPG..

Fig

  Fig.2.-Photon-stimulated spectra of 15 N 2 and 13 CO from a mixed 13 CO: 15 N 2 30 ML eq ice, in proportion 1:1, compared with a linear combination of PSD spectra obtained from pure 13 CO ice (× 0.5) and pure 15 N 2 ice (× 0.5). The spectra have been acquired from ices deposited on HOPG kept at 15 K..

Fig. 3 .

 3 Fig.3.-Photon-stimulated desorption spectra of 13 CO (left) and 15 N 2 (right) from 25 ML eq of 13 CO ice covered by an increasing 15 N 2 layer on top. The PSD spectrum obtained from a pure 25 ML eq 15 N 2 ice is also presented for comparison. All spectra are recorded for 15 K ices, deposited on HOPG..

Fig. 4 .

 4 Fig. 4.-Photon-stimulated desorption spectra of 15 N 2 (left) and 13 CO (right) from 25 ML eq of 15 N 2 ice covered by an increasing layer of 13 CO ice on top. All spectra are recorded for 15 K ices, deposited on HOPG. The top spectra of the left panel (photodesorption of N 2 from a pure N 2 ice) has been multiplied by 0.1 to facilitate the reading. In the right panel, the CO PSD spectra in the 12.3 -13.5 eV energy range have been multiplied by 3.

Fig

  Fig. A.-Mass spectra obtained from introduced partial pressure of (i ) ∼ 10 -9 Torr of 15 N 2 , (ii ) ∼ 10 -9 Torr of 13 CO, and (iii ) a mixture of ∼ 10 -9 Torr of 15 N 2 + ∼ 10 -9 Torr of 13 CO..

A. Appendix: Separation by mass spectrometry of 15 N 2 and 13 CO signals

The study of the photodesorption of N 2 and CO from mixed ice requires a fine separation of the gas phase signals associated with each molecule. In their most abundant isotopic form, 14 N 2 and 12 C 16 O, both species have the same mass, and cannot be separated by mass spectrometry. We therefore have used the isotopologues 13 C 16 O and 15 N 2 with respective mass 29 uma and 30 uma. To ensure that the rise of one given mass signal does not lead to the artificial increase of the neighbouring mass channel, it is necessary to check that the width of each mass signal is narrow enough to prevent significant overlap between the associated mass peaks. Figure A shows mass spectra, i.e. signal of the singly ionized gas phase species as a function of its mass, realized when a pressure of (i ) pure 15 N 2 , (ii ) pure 13 CO, and (iii ) mixed 13 CO: 15 N 2 in proportion 1:1, is introduced into the chamber. The mass peaks of 15 N 2 (m = 30 uma) and 13 CO (m = 29 uma) are clearly separated. The rise of one mass signal does not lead to a measurable increase of the other mass channel. Moreover, the mass spectrum associated with the gaseous mixture exhibits no overlap between the two mass peaks. In the photodesorption experiments that are presented, the signals on the mass channel 29 uma or 30 uma can therefore be associated without ambiguity to the presence into the gas of 13 CO or 15 N 2 , respectively.