From Cosmic Web to Galaxies: Tracing Gas Accretion at High Redshift through Observations and Simulations
This thesis aims to develop an integrated understanding of high-redshift galaxies within their large-scale structures. We will investigate how feedback and nuclear activity from these galaxies affect their environments by coupling observational data with cosmological simulations.
Our primary objectives are to:
1. Advance the diagnostic capabilities for studying diffuse gas.
2. Test and validate current paradigms of gas accretion.
Our observational work will utilize new data from Keck and the Very Large Telescope on Lyman-alpha halos around massive groups and clusters at z>2, which are already largely in hand. We will also incorporate a growing body of data from the James Webb Space Telescope (JWST) on the same targets to reveal the properties of galaxies and their active galactic nuclei (AGNs).
On the theoretical side, we will use publicly available results from the TNG100, HORIZON5, and CALIBRE simulations to understand galaxy evolution, learning from both the successes and failures in the comparison with observations. Ultimately, this will allow us to inform new, high-fidelity simulations of the circum-galactic medium, designed specifically to constrain gas accretion processes.
This research directly supports our long-term goal of preparing for the exploitation of BlueMUSE, a new instrument being built for the VLT, in which we participate. It will also address one of the key open questions in astrophysics, as highlighted by the Astro2020 Decadal Survey.
Multi-Probe Cosmological Mega-Analysis of the DESI Survey: Standard and Field-Level Bayesian Inference
The large-scale structure (LSS) of the Universe is probed through multiple observables: the distribution of galaxies, weak lensing of galaxies, and the cosmic microwave background (CMB). Each probe tests gravity on large scales and the effects of dark energy, but their joint analysis provides the best control over nuisance parameters and yields the most precise cosmological constraints.
The DESI spectroscopic survey maps the 3D distribution of galaxies. By the end of its 5-year nominal survey this year, it will have observed 40 million galaxies and quasars — ten times more than previous surveys — over one third of the sky, up to a redshift of z = 4.2. Combining DESI data with CMB and supernova measurements, the collaboration has revealed a potential deviation of dark energy from a cosmological constant.
To fully exploit these data, DESI has launched a “mega-analysis” combining galaxies, weak lensing of galaxies (Euclid, UNIONS, DES, HSC, KIDS) and the CMB (Planck, ACT, SPT), aiming to deliver the most precise constraints ever obtained on dark energy and gravity. The student will play a key role in developing and implementing this multi-probe analysis pipeline.
The standard analysis compresses observations into a power spectrum for cosmological inference, but this approach remains suboptimal. The student will develop an alternative, called field-level analysis, which directly fits the observed density and lensing field, simulated from the initial conditions of the Universe. This constitutes a very high-dimensional Bayesian inference problem, which will be tackled using recent gradient-based samplers and GPU libraries with automatic differentiation. This state-of-the-art method will be validated alongside the standard approach, paving the way for a maximal exploitation of DESI data.
TRANSFORMER: from the genealogy of dark matter halos to the baryonic properties of galaxy clusters.
The thesis proposes to predict the baryonic properties of galaxy clusters based on the history of dark matter halo formation, using innovative neural networks (Transformers). The work will involve intensive numerical simulations. This project falls within the general framework of determining cosmological parameters through the observation of galaxy clusters in X-rays. It is directly linked to the international Heritage programme in the XMM-Euclid FornaX deep field.
Joint simulation-based inference of tSZ maps and Euclid's weak lensing
Context:
The Euclid mission will provide weak lensing measurements with unprecedented precision, which have the potential to revolutionise our understanding of the Universe. However, as the statistical uncertainties decrease, controlling systematic effects becomes even more crucial. Among these, baryonic feedback, which redistributes gas within galaxies and clusters, remains one of the key astrophysical systematic effects limiting Euclid’s ability to constrain the equation of state of dark energy. Understanding baryonic feedback is one of the urgent challenges of cosmology today.
The thermal Sunyaev-Zel’dovich (tSZ) effect provides a unique window into the baryonic component of the Universe. This effect arises from the scattering of cosmic microwave background (CMB) photons by hot electrons in galaxy groups and clusters. This is the same hot gas that has been redistributed by baryonic feedback and is particularly relevant for weak lensing cosmology. The cross-correlation between tSZ and weak lensing (WL) probes how baryons trace and modify the cosmic structures, allowing joint constraints on cosmology and baryonic physics.
Most current tSZ-WL analyses rely on fitting angular power spectra under the assumption of a Gaussian likelihood. However, the tSZ signal is highly non-Gaussian, as it traces the massive structures of the Universe, and the power spectra fail to fully capture the information in the data. To unlock the scientific potential of the tSZ-WL analyses, it is essential to move beyond these simplifying assumptions.
PhD thesis:
The goal of this PhD project is to develop a novel simulation-based framework to jointly analyse tSZ and Euclid’s WL data. This framework will combine physically motivated forward models with advanced statistical and machine-learning techniques to provide accurate measurements of baryonic feedback and cosmological parameters. By jointly analysing tSZ and WL measurements, this project will increase the accuracy of Euclid’s cosmological analyses and improve our understanding of the dark matter-baryon connection.
Machine-learning methods for the cosmological analysis of weak- gravitational lensing images from the Euclid satellite
Weak gravitational lensing, the distortion of the 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 statistical analysis of lensing distortions can reveal the dark-matter distribution on large scales, The European space satellite Euclid will measure cosmological parameters to unprecedented accuracy. To achieve this ambitious goal, a number of sources of systematic errors have to be quanti?ed and understood. One of the main origins of bias is related to the detection of galaxies. There is a strong dependence on local number density and whether the galaxy's light emission overlaps with nearby objects. If not handled correctly, such ``blended`` galaxies will strongly bias any subsequent measurement of weak-lensing image distortions.
The goal of this PhD is to quantify and correct weak-lensing detection biases, in particular due to blending. To that end, modern machine- and deep-learning algorithms, including auto-differentiation techniques, will be used. Those techniques allow for a very efficient estimation of the sensitivity of biases to galaxy and survey properties without the need to create a vast number of simulations. The student will carry out cosmological parameter inference of Euclid weak-lensing data. Bias corrections developed during this thesis will be included a prior in galaxy shape measurements, or a posterior as nuisance parameters. This will lead to measurements of cosmological parameters with a reliability and robustness required for precision cosmology.
Methods for the Rapid Detection of Gravitational Events from LISA Data
The thesis focuses on the development of rapid analysis methods for the detection and characterization of gravitational waves, particularly in the context of the upcoming LISA (Laser Interferometer Space Antenna) space mission planned by ESA around 2035. Data analysis involves several stages, one of the first being the rapid analysis “pipeline,” whose role is to detect new events and to characterize them. The final aspect concerns the rapid estimation of the sky position of the gravitational wave source and their characteristic time, such as the coalescence time in the case of black hole mergers. These analysis tools constitute the low-latency analysis pipeline.
Beyond its value for LISA, this pipeline also plays a crucial role in the rapid follow-up of events detected by electromagnetic observations (ground or space-based observatories, from radio waves to gamma rays). While fast analysis methods have been developed for ground-based interferometers, the case of space-borne interferometers such as LISA remains an area to be explored. Thus, a tailored data processing method will have to consider the packet-based data transmission mode, requiring event detection from incomplete data. From data affected by artifacts such as glitches, these methods must enable the detection, discrimination, and analysis of various sources.
In this thesis, we propose to develop a robust and effective method for the early detection of massive black hole binaries (MBHBs). This method should accommodate the data flow expected for LISA, process potential artifacts (e.g., non-stationary noise and glitches), and allow the generation of alerts, including a detection confidence index and a first estimate of the source parameters (coalescence time, sky position, and binary mass); such a rapid initial estimate is essential for optimally initializing a more accurate and computationally expensive parameter estimation.
Unveiling the Universal Coupling Between Accretion and Ejection: From Microquasars to Extragalactic Transients
This PhD project investigates the universal coupling between accretion and ejection, the fundamental processes through which black holes and neutron stars grow and release energy. Using microquasars as nearby laboratories, the project will study how variations in accretion flows produce relativistic jets, and how these mechanisms scale up to supermassive black holes in tidal disruption events (TDEs).
Accretion–ejection coupling drives energy feedback that shapes galaxy formation and evolution, yet its physical origin remains poorly understood. The candidate will combine multi-wavelength observations—from SVOM (X-ray/optical) and new radio facilities (MeerKAT, SKA precursors)—to perform time-resolved analyses linking accretion states to jet emission.
Recent missions such as Einstein Probe and the Vera Rubin Observatory (LSST) will greatly expand the sample of transients, including jetted TDEs, enabling new tests of jet-launching physics across mass and time scales.
Working within the CEA/IRFU team, a major SVOM partner, the student will participate in real-time transient detection and multi-wavelength follow-up, while also exploiting archival data to provide long-term context. This project will train the candidate in high-energy astrophysics, radio astronomy, and data-driven discovery, contributing to a unified understanding of accretion, jet formation, and cosmic feedback.
Magnetar formation: from amplification to relaxation of the most extreme magnetic fields
Magnetars are neutron stars with the strongest magnetic fields known in the Universe, observed as high-energy galactic sources. The formation of these objects is one of the most studied scenarios to explain some of the most violent explosions: superluminous supernovae, hypernovae, and gamma-ray bursts. In recent years, our team has succeeded in numerically reproducing magnetic fields of magnetar-like intensities by simulating dynamo amplification mechanisms that develop in the proto-neutron star during the first seconds after the collapse of the progenitor core. However, most observational manifestations of magnetars require the magnetic field to survive over much longer timescales (from a few weeks for super-luminous supernovae to thousands of years for Galactic magnetars). This thesis will consist of developing 3D numerical simulations of magnetic field relaxation initialized from different dynamo states previously calculated by the team, extending them to later stages after the birth of the neutron star when the dynamo is no longer active. The student will thus determine how the turbulent magnetic field generated in the first few seconds will evolve to eventually reach a stable equilibrium state, whose topology will be characterized and compared with observations.
Exoplanets: phase curves observed by JWST
The James Webb Space Telescope (JWST), launched by NASA on December 25, 2021, is revolutionizing our understanding of the cosmos, particularly in the field of exoplanets. With more than 6,000 exoplanets detected, a great variety of worlds have been discovered, some with no equivalent in our Solar System, such as « hot Jupiters » or « super-Earths ». JWST now enables detailed characterization of exoplanetary atmospheres thanks to its spectroscopic instruments covering wavelengths from 0.6 to 27 µm and its large light-collecting area (25 m²). This capability allows determination of molecular composition, the presence of clouds or aerosols, the pressure–temperature profile, and the physical and chemical processes at work in these atmospheres.
The main method used is the so-called transit method, which observes variations in brightness when a planet passes in front of or behind its star (secondary eclipse). Nevertheless, observations over the entire orbital period (phase curve)—which also includes a transit and two eclipses—provide even more information. With phase curves, the energy budget, longitudinal structure, and atmospheric circulation can be directly observed. JWST has already obtained phase-curve data of exceptional quality. Many of these datasets are now publicly available and contain a wealth of information, though they are only partially exploited. The length of these observations, the extremely faint signals (a few tens of ppm), and the presence of subtler instrumental effects make the analysis of these data more complex.
The proposed PhD will first focus on studying and correcting these instrumental effects, then on extracting atmospheric properties using the TauREx software (https://taurex.space/), under the co-supervision of Quentin Changeat (University of Groningen) and Pierre-Olivier Langage (CEA Paris-Saclay). This PhD will contribute to preparing the scientific exploitation of the ESA Ariel mission (launch planned for 2031), entirely dedicated to the study of exoplanetary atmospheres and expected to observe nearly 50 phase-curves.
Magneto-convection of solar-type stars: flux emergence and origin of starspots
The Sun and solar-type stars possess rich and variable magnetism. In our recent work on turbulent convective dynamos in this type of star, we have been able to highlight a magneto-rotational history of their secular evolution. Stars are born active with short magnetic cycles, then slow down due to braking by their magnetized particle wind, their magnetic cycle lengthens to become commensurate with that of the Sun (lasting 11 years) and finally, for stars that live long enough, they end up with a loss of cycle and a so-called anti-solar rotation (slow equator/fast poles). The agreement with observations is excellent, but we are missing an essential element to conclude: What role do sunspots/starspots play in the organization of the magnetism of these stars, and are they necessary for the appearance of a stellar magnetic cycle, e.g. the so-called “paradox of spotty dynamos”? Indeed, our HPC simulations of solar dynamos do not have yet the angular resolution to resolve the spots, and yet we do observe cycles in our simulations of stellar dynamos for Rossby numbers < 1. So, are the spots simply a surface manifestation of an internal self-organization of the cyclic magnetism of these stars, or do they play a decisive role? Furthermore, how do the latitudinal flux emergence and the size and intensity of the spots forming on the surface evolve during the magneto-rotational evolution of these stars? To answer these key questions in stellar and solar magnetism in support of the ESA space missions Solar Orbiter and PLATO, in which we are involved, new HPC simulations of stellar dynamos must be developed, allowing us to get closer to the surface and thus better describe the process of magnetic flux emergence and the possible formation of sun/starspots. Recent tests showing that magnetic concentrations inhibiting local surface convection form in simulations with a higher magnetic Reynolds number and smaller-scale surface convection strongly encourage us to continue this project beyond the ERC Whole Sun project (ending in April 2026). Thanks to the Dyablo-Whole Sun code that we are co-developing with IRFU/Dedip, we wish to study in detail the convective dynamo, the emergence of magnetic flux, and the self-consistent formation of resolved spots, using its adaptive mesh refinement capability while varying global stellar parameters such as rotation rate, convective zone thickness, and surface convection intensity to assess how their number, morphology and latitude of emergence change and if they contribute or not to the closing of the cyclic dynamo loop.