PhD subjects

We now know that the first massive groups and clusters were already forming in the first 2-3 billion years of the Universe’s history. Unlike their modern-day descendants, these fascinating systems contained often highly star-forming gas-rich galaxies that later on quenched (stopped forming stars) and transformed morphologically into ellipticals systems through processes that are not yet fully known. This include the recent discovery of peculiar systems with quenched disks and star-forming bulges, which could be seen as ‘anti-galaxies’ respect to the later-time typical objects that are quenched in the centres (bulges) and forming stars in the disks (like our Milky-Way Galaxy). Other exotic components that have been recently discovered are giant reservoirs of cold diffuse hydrogen, possibly connected to cold streams postulated by theory and never fully confirmed, and intracluster light, probably related to early phases of galaxy interactions and mergers that stand in contradiction with current model predictions. The Euclid satellite, with a strong participation from France and CEA/AIM, will be launched in 2023, and will provide ideal ultra-deep multi-wavelength imaging in the optical and near-IR, together with ancillary data at longer wavelengths, to identify the first generation of galaxy groups and clusters that started forming in the distant Universe and study the different exciting physical phenomena that are occurring in dense environments at early times. The PhD student will join Euclid teams and will lead research into these problematics in collaboration with the group in CEA Saclay.

Weak gravitational lensing, the distortion of images of high-redshift galaxies due to foreground matter structures on large scales, is one of the most promising tools of cosmology to probe the dark sector of the Universe.



The student will work on various wide-field instruments which provide imaging surveys of galaxies:

- UNIONS, the Ultraviolet Near-Infrared Optical Northern Sky survey, an ongoing large imaging survey of the Northern sky in 5 bands.

- WFST, the Wide-Field Survey Telescope. This 2.5m optical telescope under construction in China will observe the Northern sky in 5 bands.

- CSST, the 2m Chinese Space Station Telescope, to be launched in 2024 into a low Earth orbit, will observe an area of 17,500 deg2 in 7 optical and near-UV bands.



Starting with ShapePipe, a weak-lensing pipeline created by our group, the student will develop new methods to analyse such large

datasets. The unprecedented statistical precision will require novel approaches for quantifying observational and instrumental systematic errors. Astrophysical and cosmological observables will be modeled carefully for robust and reliable inference of dark-matter and dark-energy properties from weak-lensing data.

The aim of this thesis is to explore the Universe at low surface brightness on a large sample of galaxies in the nearest cosmic filaments (z<0.1) by exploiting the unique imaging and spectroscopy capabilities of Euclid, a mission that will be launched in 2023 by the European Space Agency and in which France is heavily involved. Cosmological simulations and theoretical models predict a morphological segregation of galaxies at the edge and within the large filaments that form the cosmic web, as well as notable correlations between their orientation and that of the large cosmic filaments. This segregation results from tidal effects via i) the infall of galaxies towards the gravitational potential wells caused by the dark matter of the filaments and ii) the flow of galaxies within these same filaments. To date, this signature has not been explored in depth in the nearby Universe because of a lack of an adequate large imaging+spectroscopic survey. However, understanding these intrinsic alignments of galaxies has a twofold interest, not only to understand the formation and evolution of galaxies as such (nature vs nurture) but also because these alignments contaminate the cosmic shear signal which is measured from coherent deformations of the shapes of galaxies. Thus, the Euclid space telescope will constrain the evolution models of the Universe while providing evidence on the intrinsic alignments of galaxies which affect at higher redshift the measurements of gravitational shear at the heart of the Euclid’s core science on the question of dark energy. Recent advances in the exploration of the outer regions of galaxies indicate that the morphology inferred from the central, bright, section generally does not reflect the one derived from the outermost regions related to the halo. These outer regions are a tracer of the evolution over the last billion years during which galaxies have evolved within, or near, a large structure, the interactions between galaxies in the filament representing a nuisance factor. The nearby Universe is the ideal laboratory because the cosmological extinction still has little effect on the measurement of the faint brightness of the external regions of the galaxies. Euclid will provide a unique sample of galaxies whose membership in filaments will be guaranteed by spectroscopy while its imaging capabilities at low surface brightness from the optical to the near-infrared (a whole new observation window ideal for capturing the old stellar population from the outer regions) will reveal the morphology at the true edges of the galaxies. This project is a rare case in the Euclid legacy science making a critical use of all three instrumental modes, exploiting the VIS, Y, H, J imaging and the spectroscopy. Before focusing this study on the Euclid data which will arrive in 2024, the first part of the thesis will consist in a pilot study based on data from the CFIS-UNIONS northern sky survey carried out with the MegaCam camera on the Canada-France-Hawaii Telescope. This ground-based survey spawned from the need of securing photometric data to derive photometric redshifts for Euclid but it also carries a diverse galactic and extragalactic science that stands on its own merit. The pilot study will exploit this deep optical dataset optimized for low surface brightness studies in particular, over an area that covers the nearest dense filament, the Pisces-Perseus supercluster at z=0.02 covering 80 degrees (!) in the sky. The full imaging dataset has now been acquired over this region of interest and is ready for analysis in the context of a thesis effort. Spectroscopic redshifts are available for nearly two thousand galaxies from the Sloan surveys and the HI Arecibo Legacy Fast ALFA Survey. The CFIS-UNIONS survey, just as Euclid will, also probes the large voids around the filament, thus completing the comparison of morphology segregation of galaxies directly linked to the filament.

The intergalactic magnetic field pervading the cosmic voids is suspected to be a relic field originating from the very first epoch of the cosmic history. The goal of this PhD is to look for signatures of this field in the high-energy data of gamma-ray bursts, and to predict the ability of the future CTA observatory to constrain its properties. This work combines both theoretical modelling and analysis of simulated CTA data.

Exoplanets are now observed in large numbers and around stars with varied properties. Cradles of life development, it is essential to understand the physical processes leading to their formation but also the initial conditions that prevail during the very first steps of their assembly in order to constrain the models of planetary genesis.

Recent observations of protopanetary disks suggest that some planets may already be formed around very young stars, only one million years after the beginning of the star formation process: it seems therefore crucial to explore the earliest phases of solar-type star formation in search of signatures of dust assembly into small planetesimals.

Recently, our team obtained first observational evidence that dust particles around the youngest protostars in our Galaxy might have already evolved significantly with grains perhaps already a few microns large. If these results are confirmed, then the scenario of planetesimal formation will have to be revisited by taking into account the impact of these initial conditions very different from those prevailing in the disks around T-Tauri stars, during the first phase of dust growth.



The subject of this thesis is part of a concerted approach using observations and models to characterize the size of dust grains around protostars only a few hundred thousand years old.

It will analyze data sets obtained with the ALMA radio telescope to measure the spectral indices of the continuum emission of dust grains surrounding Class 0 and I protostars.

Complementary constraints will be obtained at millimeter wavelengths thanks to polarimetric data from a large program of observations with the NOEMA telescope, very sensitive to the size of the largest dust grains.

Our collaboration is currently implementing a new dust model better adapted to the dense gas which, coupled to a radiative transfer code, will allow us to directly compare these observational data to synthetic predictions from MHD models of protostellar evolution.

Cosmology in the 21st century aims to better our understanding of the Universe by seeking to answer open questions concerning the nature of dark matter and dark energy, and the precise expansion rate of the Universe. In order to tackle these questions, it is essential to take advantage of all the data made available in the current era of multi-messenger astronomy, capitalising on the latest advances in signal processing, machine learning and the handling of big data.

Current and upcoming optical surveys, such as KiDS-450 [1], the Dark Energy Survey Year 1 [2], the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) [3] and Euclid [4], are probing wider and deeper patches of the late-time Universe to improve constraints on cosmological parameters by measuring the shapes and distributions of galaxies. These parameters can be compared to the latest analyses of the cosmic microwave background radiation (i.e. the early Universe) by surveys like Planck [5]. Recent studies [6] highlight some discrepancy between early and late-time analyses indicating some systematic uncertainty or an incomplete model of cosmology.

Additionally, In recent years gravitational wave interferometers, such as LIGO and Virgo, have pushed astronomical observations beyond the electromagnetic spectrum. This has made it possible to detect the interaction of distant neutron stars and black holes.

Radio wavelengths provide a complementary and independent probe of the late-time Universe. Radio astronomy provides the advantage of probing higher redshifts, having a deterministic point spread function (PSF) and being less sensitive to PSF anisotropies [7]. Cross-correlations between radio and optical surveys can additionally alleviate systematics effects such as intrinsic alignments improving cosmological constraints [8-9]. Upcoming radio surveys, such as the Square Kilometre Array (SKA), are designed to reach an order of magnitude greater sensitivity and survey speed than existing instruments. SKA has the potential to add significant additional constraints on cosmological parameters given the vast sky area it will cover (~75%). This, however, comes at the cost of having to manage extremely large scales of data and complicated image reconstruction. SKA is expected to produce ~1 TB of data every second. With typical observations taking ~6h and a total lifespan of 15 years, SKA will produce data in the Exabyte (1018 bytes) scale [10], making it one of the biggest data management problems in modern science.

The CosmoStat team has been pioneering the use of signal processing and machine learning techniques for solving inverse problems in astronomical image reconstruction. Applying these methods to radio-interferometric data, however, brings a host of new challenges, in part due to the additional complexity of the inverse problems to solve, but also due to the extremely large-scale dimensions of the problem. Conventional deep learning approaches will not be able to scale to the typical size of an SKA field, and developing efficient model-parallelism approaches will be necessary.

X-ray binaries (or microquasars) represent excellent laboratories for testing physical phenomena in the most extreme environments. Composed of a compact star (black hole or neutron star) accreting matter from a companion star, they have been observed for several years at various wavelengths, allowing to characterize a set of complex activities. A very varied physics is thus opened to the modelers.



The goal of this thesis will be to study the activities of binary black holes recently discovered in our Galaxy. The main objective is to understand the connections between accretion and ejection processes, but more particularly to constrain the energy of their relativistic jets from calorimetric measurements made during their interactions with the surrounding medium. The modeling of such interactions brings new constraints on the energy balance of black holes, information that is essential for the understanding of these systems.

The goal of this PhD project is to develop all necessary tools for an efficient and reliable analysis of Euclid weak-lensing and lensing - galaxy cross-correlation data. Starting from the measured Euclid weak-lensing galaxy shapes and spectroscopic galaxy data from Euclid and other surveys such as BOSS, eBOSS, and DESI, the student will construct various estimators of lensing and cross-correlation observables.

Combinations of these observables as function of scale, redshift, and galaxy properties will be optimised to maximally extract cosmological information from the data. In addition, detailed modelling of systematic effects will be carried out to control and minimize their influence on the results.



The student will make use of, and further develop modern statistical inference tools for efficient parameter inference. Theoretical predictions of observables from models of the expansion history and large-scale structure of the Universe will be created in an automatic differentiation framework, e.g. using the library jaxcosmo, exploiting massive parallel computations on GPUs and the ability to compute

gradients of the likelihood to accelerate inference. This will open up efficient (Bayesian) inference methods that make use of the gradients of the models with respect to parameters. Compared to traditional sampling techniques, these methods offer a significant computation time speed-up, and the ability to efficiently explore a large number of parameters. This is important for exploring non-standard models of gravity with additional parameters, and flexible models with many nuisance parameters. It also allows us to include detailed, time-consuming modelling of systematic and higher-order effects.

The InterStellar Medium (ISM) is the complex intertwining of phases filling the volume of a galaxy between the stars. It is constituted of: (i) gas, principally hydrogen (75%) and helium (23%), but also heavier elements (C, N, O, etc.; 1%) that can be found in molecular forms; and (ii) dust grains (the remaining 1% of the ISM mass), which are small solid particles of sub-micronic sizes. The ISM is a fundamental constituent of the Universe, as stars are born out of the collapse of dense interstellar clouds, and return some of their mass, enriched in freshly synthesized heavy elements, at the end of their lifetime.



Interstellar dust is particularly important component of the ISM, as it absorbs the visible light and reemits it thermally in the infrared. Certain interstellar regions are totally opaque to visible photons and can only be probed by their infrared emission. In addition, dust is an important agent of the gas heating, by photoelectric effect. It is also the catalyst where dihydrogen, the most abundant molecule in the Universe, forms. Yet, interstellar grain properties (composition, abundance, size distribution, etc.) are still poorly known. This uncertainty thus impedes our understanding of the physics of the ISM, and by extension, of galaxy evolution.



This thesis project aims to progress in our understanding of grain properties, focusing on the variation of these properties in the nearby Universe. Dust indeed evolves in the ISM, and this evolution depends on local conditions (gas density, UV field, etc.). This evolution can be studied in an empirical way, modeling multiwavelength observations, spatially-resolved at the scale of a few hundred parsecs, in nearby galaxies.



Our group has a renowned expertise in this area. We are currently leading a large millimeter observation program of these objects, with the instrument NIKA2 (https://irfu.cea.fr/dap/Phocea/Vie_des_labos/Ast/ast_visu.php?id_ast=4644). We have recently been instrumental in modeling spectral energy distributions for the large European collaboration, DustPedia (http://dustpedia.astro.noa.gr/?AspxAutoDetectCookieSupport=1). We have also developed a unique spectral energy distribution fitting code, implementing a hierarchical Bayesian method, HerBIE (Galliano, 2018 ; https://ui.adsabs.harvard.edu/abs/2018MNRAS.476.1445G/abstract). This code allowed us to estimate the characteristic timescales of cosmic dust evolution (https://irfu.cea.fr/dap/Phocea/Vie_des_labos/Ast/ast.php?t=fait_marquant&id_ast=4929).



The thesis work will have two parts. The first task will consist in developing the HerBIE code, implementing the emission from stellar populations. Besides, this modeling will need to be executed self-consistently with the chemical evolution computation. We will also need to model the radiative transfer through the ISM, in a large number of possible topologies. The second part will consist in applying this code to multiwavelength observations of nearby galaxies, in order to demonstrate trends between grain properties and the physical conditions of the ISM, and constrain dust evolution processes.

While the Universe is expanding with increasing velocity, the question of what is causing cosmic acceleration remains unsolved. Acceleration seems to act against gravitational attraction, as if a new source of energy, dubbed dark energy, were responsible for it. In addition, neutrino masses are yet to be measured and are degenerate with dark energy evolution.



This PhD proposal is meant to contribute to the Euclid mission, by combining information from galaxy clustering and weak lensing, and integrate it in the Euclid Consortium validated likelihood.

The PhD student will be able to work at the interface between data and theory and concretely collaborate with a large collaboration like the Euclid satellite. Objectives include 1) extending the likelihood software to include early dark energy models 2) contribute to the collaboration effort on comparing theoretical predictions with data and the cross-correlation between galaxy clustering and weak lensing 3) investigate different survey samples and statistics to break the degeneracy between neutrino masses and dark energy evolution.

The interaction of convective motions in the outer convective layer of Sun-like stars with the rotation and the magnetic field is at the origin of the appearance of a dynamo which is responsible for the cycles of magnetic activity. These cycles produce periods of high activity alternated by other less active. This magnetic activity is very important to understand the development and establishment of life as we know it on Earth and to improve the detectability of planets around active stars. Indeed, one of the most important sources of noise to be able to detect and characterise the atmospheres of low-mass planets like the Earth around stars like the Sun is related to the magnetic variability. A better understanding and characterization of this variability is therefore extremely important for the scientific exploitation of data collected by space missions such as Kepler, TESS or JWST of NASA as well as the future satellites PLATO and ARIEL of ESA on which the DAp/CEA is strongly involved in its development and exploitation. Thanks to more than 25 years of data obtained by the ESA/NASA SoHO satellite (still flying around the Sun), the student will start by characterizing seismically the variations of the outermost layers of the Sun during the last two activity cycles (23 and 24) covering already more than 26 years.

The second part of the thesis will consist in searching for activity cycles in the data of ~160,000 stars observed during 4 years by the Kepler satellite and thus better prepare the necessary tools (including "Machine Learning" techniques) to obtain these cycles in the data of the NASA TESS mission and for the future ESA PLATO mission. In parallel to these studies, the student will participate in the characterization of the noise of planetary stars candidates for planetary atmosphere studies with JWST and ARIEL, in collaboration with other members of LDE3, to better characterise the modulations associated with the rotation and magnetism of these stars and thus to improve the characterization of planetary atmospheres. These studies could be done with TESS or ground-based follow-up data.

With ~5,000 exoplanets known (http://exoplanet.eu), it is clear that the observed diversity of exoplanets is linked to their histories. In this setting, exoplanet science is faced with two key questions. The first one is how evolution may have modified the planets’ bulk compositions. The question is timely as various facilities (JWST, launch date: December 2021; ARIEL, launch in 2028; E-ELT: first light in 2027) will study in unprecedented detail the atmospheres of exoplanets with spectroscopy. The second question is how evolution may have shaped the demographics of exoplanets. Notably, our grasp of demographics has changed radically in the last decade, and will continue evolving thanks to new discoveries from photometric space missions (e.g. TESS, PLATO) and radial velocity surveys on the main ground-based telescopes.

Digesting that empirical knowledge requires physically-motivated models that connect the properties of the planets and their host stars throughout their shared histories. To that end, our project will build a sophisticated treatment of radiative transfer (RT) for close-in exoplanets with both hydrogen- and non-hydrogen-dominated atmospheres. The RT modules will be implemented into the team’s photochemical-hydrodynamic models to better understand the temporal evolution of the exoplanets. The predictions will help interpret the constraints that JWST will set on the composition of a few small exoplanets for which observing time has been granted as part of GTO+GO programs.

The James Webb Space Telescope (JWST) is revolutionizing our knowledge of exoplanets. Thanks to its large collecting area (25 m2) and its capacity for spectroscopic observations in a wide range of wavelengths (0.6 - 28 microns), the telescope can probe the atmosphere of a wide range of exoplanets, ranging from warm Jupiters to temperate rocky planets. Thanks to our strong involvement in the development of the JWST Mid-InfraRed Instrument (MIRI), we have guaranteed observing time and coordinate the programme dedicated to the observation of exoplanets. The data provided by the JWST are of remarkable quality.



The thesis work will consist of reducing, analyzing and interpreting the data provided by the JWST during cycle 1 and cycle 2, preparing time requests for cycles 3 and 4 from simulated observations. The laboratory is also very involved in the Ariel mission. One aspect of the thesis will be the study of synergies between JWST and Ariel.

The scientific objective of the Franco-Chinese SVOM satellite, whose launch is scheduled for the end of 2023 in phase with the start of the proposed thesis, is the study of gamma-ray bursts (GRBs), ephemeral astrophysical events in the sky, releasing tremendous energy as bursts of gamma rays from a point in the sky. Previous missions focused on the detection of short GRBs with average durations of 1 s (resp. long GRBS, emitting for around 10 s), associated with the coalescence of compact objects such as neutron stars (resp. supernovae of very massive stars). Very promising targets for SVOM are the class of ultra-long GRBs (with a gamma emission up to 10000 s and whose origin remains an enigma), and GRBs at cosmological distances (with a high redshift, and therefore detectable in the low-energy range). The ECLAIRs telescope on board SVOM is particularly well suited to observing this type of burst, thanks to its detection threshold as low as 4 keV and thanks to the gamma-ray burst "trigger", the scientific software on board ECLAIRs, developed at CEA. This trigger detects and localizes gamma-ray bursts on board the satellite, requests its repointing for follow-up observations with the other instruments on board, and alerts the ground community of the occurrence of the event. The thesis proposes the study of the first gamma-ray bursts observed by the ECLAIRs instrument operational in flight, in particular the long and ultra-long duration bursts and the bursts rich in X-rays. The thesis candidate will take part in the observation campaigns and analyze the data produced by the instrument. In particular, the understanding of the background noise observed at low energy, including the known sources referenced in an onboard catalog, and the scientific analysis of the operation of the trigger on time scales ranging from 20 s to 20 min are crucial to increase the number of triggers on these innovative sources.