Probing quantum information with the top quark at the LHC
This PhD project aims to explore the quantum nature of top-quark pair production at the Large Hadron Collider by studying spin correlations and entanglement-related observables in data recorded by the ATLAS experiment. The recent breakthrough observations of entanglement in top-antitop events have opened an entirely new window onto the quantum structure of fundamental interactions, transforming the LHC into a machine to test quantum information at the TeV scale. Building on this momentum, the thesis will focus on reconstructing the quantum state of top-quark pairs using ATLAS Run-3 data, with particular attention to the extraction of spin correlations and entanglement-sensitive observables in challenging high-momentum topologies. By improving reconstruction strategies and carefully assessing detector effects, the aim is to measure quantum properties with good precision and to contribute to understand what quantum information can bring us to our understanding of elementary particles.
Lightweight and high-strength metamaterials with innovative architectures manufactured by additive manufacturing for constrained environments
Environmental constraints, rising raw material costs, and the need to reduce carbon footprints drive the development of more porous materials that combine lightness with mechanical strength. Such materials meet the requirements of strategic sectors including aerospace, space, transportation, energy, and high-performance physics instruments.
Mechanical metamaterials, composed of micro-lattice structures produced by 3D printing, offer a unique potential to address these challenges. By tailoring the topology of their internal networks, it becomes possible to achieve stiffness-to-density ratios higher than those of conventional materials and to adapt their architecture to target specific mechanical or functional properties.
This thesis is part of this wave of innovation. It aims to develop ultralight metallic metamaterials whose architecture is optimized to maximize mechanical performance while maintaining isotropy, ensuring predictable behavior using conventional engineering tools, including finite element analysis, numerical simulation, and multiscale approaches. The research builds on the recognized expertise of the CEA, particularly at IRAMIS and IRFU/DIS, in designing isotropic random metastructures and shaping them through metal additive manufacturing.
By combining numerical mechanics, advanced design, multi-process additive manufacturing, and in situ characterization, this thesis seeks to push the current limits of design and fabrication of complex metallic structures.
SEARCH FOR DIFFUSE EMISSIONS AND SEARCHES IN VERY-HIGH-ENERGY GAMMA RAYS AND FUNDAMENTAL PHYSICS WITH H.E.S.S. AND CTAO
Observations in very-high-energy (VHE, E>100 GeV) gamma rays are crucial for understanding the most violent non-thermal phenomena at work in the Universe. The central region of the Milky Way is a complex region active in VHE gamma rays. Among the VHE gamma sources are the supermassive black hole Sagittarius A* at the heart of the Galaxy, supernova remnants and even star formation regions. The Galactic Center (GC) houses a cosmic ray accelerator up to energies of PeV, diffuse emissions from GeV to TeV including the “Galactic Center Excess” (GCE) whose origin is still unknown, potential variable sources at TeV, as well as possible populations of sources not yet resolved (millisecond pulsars, intermediate mass black holes). The GC should be the brightest source of annihilations of massive dark matter particles of the WIMPs type. Lighter dark matter candidates, axion-like particles (ALP), could convert into photons, and vice versa, in magnetic fields leaving an oscillation imprint in the gamma-ray spectra of active galactic nuclei (AGN).
The H.E.S.S. observatory located in Namibia is composed of five atmospheric Cherenkov effect imaging telescopes. It is designed to detect gamma rays from a few tens of GeV to several tens of TeV. The Galactic Center region is observed by H.E.S.S. for twenty years. These observations made it possible to detect the first Galactic Pevatron and place the strongest constraints to date on the annihilation cross section of dark matter particles in the TeV mass range. The future CTA observatory will be deployed on two sites, one in La Palma and the other one in Chile. The latter composed of more than 50 telescopes will provide an unprecedented scan of the region of the Galactic Center.
The proposed work will focus on the analysis and interpretation of H.E.S.S observations carried out in the Galactic Center region for the search for diffuse emissions (populations of unresolved sources, massive dark matter) as well as observations carried out towards a selection of active galactic nuclei for the search for ALPs constituting dark matter. These new analysis frameworks will be implemented for the CTA data analyses. An involvement in the commissioning of the first MSTs in Chile and in the data analysis for early science are expected.
Large scale simulation and machine learning in nucleon structure
The PhD proposal investigates the nucleon’s three-dimensional structure using Generalized Parton Distributions (GPDs). GPDs give access to the spatial distribution of quarks and gluons, the energy-momentum tensor, and thus information on spin, internal pressure, and mass. Two main challenges arise: scarce exclusive experimental data and the high cost of precise lattice-QCD simulated observables. The project comprises two parts: (I) generate new lattice-QCD simulations of GPD moments, improve algorithms, and perform continuum extrapolations; (II) create machine-learning tools to tackle the ill-posed inverse problem and conduct global fits that combine experimental and simulated data. The work will be carried out at the European Joint Virtual Lab AIDAS shared between Julich Forschungszentrum (Germany) and CEA (France), with equal time spent in each country. Required skills include quantum field theory, object-oriented programming (C++, Python), and high-performance computing. The ultimate goal is the first reliable extraction of the nucleon’s 3-D structure, informing future facilities such as the EIC and EicC.
Point Spread Function Modelling for Space Telescopes with a Differentiable Optical Model
Context
Weak gravitational lensing [1] is a powerful probe of the Large Scale Structure of our Universe. Cosmologists use weak lensing to study the nature of dark matter and its spatial distribution. Weak lensing missions require highly accurate shape measurements of galaxy images. The instrumental response of the telescope, called the point spread function (PSF), produces a deformation of the observed images. This deformation can be mistaken for the effects of weak lensing in the galaxy images, thus being one of the primary sources of systematic error when doing weak lensing science. Therefore, estimating a reliable and accurate PSF model is crucial for the success of any weak lensing mission [2]. The PSF field can be interpreted as a convolutional kernel that affects each of our observations of interest, which varies spatially, spectrally, and temporally. The PSF model needs to be able to cope with each of these variations. We use specific stars considered point sources in the field of view to constrain our PSF model. These stars, which are unresolved objects, provide us with degraded samples of the PSF field. The observations go through different degradations depending on the properties of the telescope. These degradations include undersampling, integration over the instrument passband, and additive noise. We finally build the PSF model using these degraded observations and then use the model to infer the PSF at the position of galaxies. This procedure constitutes the ill-posed inverse problem of PSF modelling. See [3] for a recent review on PSF modelling.
The recently launched Euclid survey represents one of the most complex challenges for PSF modelling. Because of the very broad passband of Euclid’s visible imager (VIS) ranging from 550nm to 900nm, PSF models need to capture not only the PSF field spatial variations but also its chromatic variations. Each star observation is integrated with the object’s spectral energy distribution (SED) over the whole VIS passband. As the observations are undersampled, a super-resolution step is also required. A recent model coined WaveDiff [4] was proposed to tackle the PSF modelling problem for Euclid and is based on a differentiable optical model. WaveDiff achieved state-of-the-art performance and is currently being tested with recent observations from the Euclid survey.
The James Webb Space Telescope (JWST) was recently launched and is producing outstanding observations. The COSMOS-Web collaboration [5] is a wide-field JWST treasury program that maps a contiguous 0.6 deg2 field. The COSMOS-Web observations are available and provide a unique opportunity to test and develop a precise PSF model for JWST. In this context, several science cases, on top of weak gravitational lensing studies, can vastly profit from a precise PSF model. For example, strong gravitational lensing [6], where the PSF plays a crucial role in reconstruction, and exoplanet imaging [7], where the PSF speckles can mimic the appearance of exoplanets, therefore subtracting an accurate and precise PSF model is essential to improve the imaging and detection of exoplanets.
PhD project
The candidate will aim to develop more accurate and performant PSF models for space-based telescopes exploiting a differentiable optical framework and focus the effort on Euclid and JWST.
The WaveDiff model is based on the wavefront space and does not consider pixel-based or detector-level effects. These pixel errors cannot be modelled accurately in the wavefront as they naturally arise directly on the detectors and are unrelated to the telescope’s optic aberrations. Therefore, as a first direction, we will extend the PSF modelling approach, considering the detector-level effect by combining a parametric and data-driven (learned) approach. We will exploit the automatic differentiation capabilities of machine learning frameworks (e.g. TensorFlow, Pytorch, JAX) of the WaveDiff PSF model to accomplish the objective.
As a second direction, we will consider the joint estimation of the PSF field and the stellar Spectral Energy Densities (SEDs) by exploiting repeated exposures or dithers. The goal is to improve and calibrate the original SED estimation by exploiting the PSF modelling information. We will rely on our PSF model, and repeated observations of the same object will change the star image (as it is imaged on different focal plane positions) but will share the same SEDs.
Another direction will be to extend WaveDiff for more general astronomical observatories like JWST with smaller fields of view. We will need to constrain the PSF model with observations from several bands to build a unique PSF model constrained by more information. The objective is to develop the next PSF model for JWST that is available for widespread use, which we will validate with the available real data from the COSMOS-Web JWST program.
The following direction will be to extend the performance of WaveDiff by including a continuous field in the form of an implicit neural representations [8], or neural fields (NeRF) [9], to address the spatial variations of the PSF in the wavefront space with a more powerful and flexible model.
Finally, throughout the PhD, the candidate will collaborate on Euclid’s data-driven PSF modelling effort, which consists of applying WaveDiff to real Euclid data, and the COSMOS-Web collaboration to exploit JWST observations.
References
[1] R. Mandelbaum. “Weak Lensing for Precision Cosmology”. In: Annual Review of Astronomy and Astro- physics 56 (2018), pp. 393–433. doi: 10.1146/annurev-astro-081817-051928. arXiv: 1710.03235.
[2] T. I. Liaudat et al. “Multi-CCD modelling of the point spread function”. In: A&A 646 (2021), A27. doi:10.1051/0004-6361/202039584.
[3] T. I. Liaudat, J.-L. Starck, and M. Kilbinger. “Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies”. In: Frontiers in Astronomy and Space Sciences 10 (2023). doi: 10.3389/fspas.2023.1158213.
[4] T. I. Liaudat, J.-L. Starck, M. Kilbinger, and P.-A. Frugier. “Rethinking data-driven point spread function modeling with a differentiable optical model”. In: Inverse Problems 39.3 (Feb. 2023), p. 035008. doi:10.1088/1361-6420/acb664.
[5] C. M. Casey et al. “COSMOS-Web: An Overview of the JWST Cosmic Origins Survey”. In: The Astrophysical Journal 954.1 (Aug. 2023), p. 31. doi: 10.3847/1538-4357/acc2bc.
[6] A. Acebron et al. “The Next Step in Galaxy Cluster Strong Lensing: Modeling the Surface Brightness of Multiply Imaged Sources”. In: ApJ 976.1, 110 (Nov. 2024), p. 110. doi: 10.3847/1538-4357/ad8343. arXiv: 2410.01883 [astro-ph.GA].
[7] B. Y. Feng et al. “Exoplanet Imaging via Differentiable Rendering”. In: IEEE Transactions on Computational Imaging 11 (2025), pp. 36–51. doi: 10.1109/TCI.2025.3525971.
[8] Y. Xie et al. “Neural Fields in Visual Computing and Beyond”. In: arXiv e-prints, arXiv:2111.11426 (Nov.2021), arXiv:2111.11426. doi: 10.48550/arXiv.2111.11426. arXiv: 2111.11426 [cs.CV].
[9] B. Mildenhall et al. “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis”. In: arXiv e-prints, arXiv:2003.08934 (Mar. 2020), arXiv:2003.08934. doi: 10.48550/arXiv.2003.08934. arXiv:2003.08934 [cs.CV].
Study of uranium-235 fission induced by neutrons from 0.5 to 40 MeV at NFS-SPIRAL2 using the FALSTAFF spectrometer and the FIFRELIN code
The presented project has two main objectives. The first one is the realization (building, calibration, data taking and data analysis) of a first experiment with the FALSTAFF detector in its configuration with two detection arms. In such a configuration, FALSTAFF will be able to detect in coincidence both fragments emitted by fast-neutron triggered fission reactions. These neutrons will be provided by the neutron beam of SPIRAL2-NFS in GANIL. The advantage of using direct kinematics is the ability to determine on an event-by-event basis the excitation energy of the fissioning nucleus by the measurement of the incident-neutron kinetic energy.
For this first experiment, we will have a uranium 235 target. 235U is the main source of fission neutrons in nuclear reactors and therefore at the heart of the system. Hence, the understanding of neutron-induced fission of 235U is essential and the rather exclusive data FALSTAFF will provide, with not only the identification of the fission fragments but also their kinematics will permit to reconstruct also the fissioning system. Such a measurmement in direct kinematics have never been done, to our knowledge, with the accuracy we are aiming at.
To perform this exepriment, we have improved and added detection capabilities to the FALSTAFF spectrometer, in particular with the financial support of the Région Normandie over the last two years. This experiment will be completed by a work to be done on a theoretical model developed by our collaborators of CEA-Cadarache. We will compare our detailled data with predictions of the model and have the model evolve, according to the laws of nuclear physics in order to obtain results from the model close to the data. Such a test of this model on as complete data as those we will obtain with FALSTAFF have never been done so far.
Precise time tagging and tracking of leptons in Enhanced Neutrino Beams with large area PICOSEC-Micromegas detectors
The ENUBET (Enhanced NeUtrino BEams from kaon Tagging) project aims to develop a monitored neutrino beam with a precisely known flux and flavor composition, enabling percent-level precision in neutrino cross-section measurements. This is achieved by instrumenting the decay tunnel to detect and identify charged leptons from kaon decays.
The PICOSEC Micromegas detector is a fast, double-stage micro-pattern gaseous detector that combines a Cherenkov radiator, a photocathode, and a Micromegas amplification structure. Unlike standard Micromegas, it operates with amplification also occurring in the drift region, where the electric field is even stronger than in the amplification gap. This configuration enables exceptional timing performance, with measured resolutions of about 12 ps for muons and ~45 ps for single photoelectrons, making it one of the fastest gaseous detectors ever developed.
Integrating large-area PICOSEC Micromegas modules in the ENUBET decay tunnel would provide sub-100 ps timing for lepton tagging, improving particle identification, reducing pile-up, and enhancing the association between detected leptons and their parent kaon decays — a key step toward precision-controlled neutrino beams.
Within the framework of this PhD work, the candidate will optimize and characterize 10 × 10 cm² PICOSEC Micromegas prototypes, and contribute to the design and development of larger-area detectors for the nuSCOPE experiment and the ENUBET hadron dump instrumentation.
Explainable observers and interpretable AI for superconducting accelerators and radioactive isotope identification
GANIL’s SPIRAL1 and SPIRAL2 facilities produce complex data that remain hard to interpret. SPIRAL2 faces instabilities in its superconducting cavities, while SPIRAL1 requires reliable isotope identification under noisy conditions.
This PhD will develop observer-based interpretable AI, combining physics models and machine learning to detect, explain, and predict anomalies. By embedding causal reasoning and explainability tools such as SHAP and LIME, it aims to improve the reliability and transparency of accelerator operations.
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.