Institute of research into the fundamental laws of the Universe

The Higgs boson, discovered in 2012 at the LHC, is at the origin of the electroweak symmetry breaking within the Standard Model (SM). Despite extensive studies on the Higgs properties, the Higgs self-coupling remains unexplored. This parameter is a key factor in determining the Higgs potential and the stability of the universe’s vacuum. Studying Higgs pair production is the only direct method for measuring this self-coupling, which will give crucial insights into the universe’s fundamental structure and the nature of the electroweak phase transition after the Big Bang. Di-Higgs production is predicted to have a very small cross-section within the SM. Among possible detection channels, the multilepton final state is promising due to its unique kinematic signature, though challenging due the need for precise lepton identification and advanced signal separation techniques using machine learning. This PhD project focuses on searching for di-Higgs production in the multilepton channel with 13.6 TeV ATLAS data, taking advantages from the increased data and energy in Run 3 and aiming to approach SM sensitivity.

Multi-wavelength observation of astrophysical sources is the key to a global understanding of the physical processes involved. Due to instrumental constraints, the spectral band from 0.1 to 1 MeV is the one that suffers most from insufficient detection sensitivity in existing observatories. This band allows us to observe the deepest and most distant active galactic nuclei, to better understand the formation and evolution of galaxies on cosmological scales. It reveals the processes of nucleosynthesis of the heavy elements in our Universe and the origin of the cosmic rays that are omnipresent in the Universe. The intrinsic difficulty of detection in this spectral range lies in the absorption of these very energetic photons after multiple interactions in the material. This requires good detection efficiency, but also good localisation of all the interactions in order to deduce the direction and energy of the incident photon. These detection challenges are the same for other applications with a strong societal and environmental impact, such as the dismantling of nuclear facilities, air quality monitoring and radiotherapy dosimetry.

The aim of this instrumentation thesis is to develop a versatile 3D detector that can be used in the fields of astrophysics and nuclear physics, with improved detection efficiency in the 100 keV to 1 MeV range and Compton events, as well as the possibility of locating interactions in the detector at better than pixel size.

Several groups around the world, including our own, have developed hard X-ray imaging spectrometers based on high-density pixelated semiconductors for astrophysics (CZT for NuSTAR, CdTe for Solar Orbiter and Hitomi), for synchrotron (Hexitec UK, RAL) or for industrial applications (Timepix, ADVACAM). However, their energy range remains limited to around 200 keV (except for Timepix) due to the thinness of the crystals and their intrinsic operating limitations. To extend the energy range beyond MeV, thicker crystals with good charge carrier transport properties are needed. This is currently possible with CZT, but several challenges need to be overcome.

The first challenge was the ability of manufacturers to produce thick homogeneous CZT crystals. Advances in this field over the last 20 years mean that we can now foresee detectors up to at least 10 mm thick (Redlen, Kromek).

The main remaining technical challenge is the precise estimation of the charge generated by the interaction of a photon in the semiconductor. In a pixelated detector where only the X and Y coordinates of the interaction are recorded, increasing the thickness of the crystal degrades spectral performance. Obtaining Z interaction depth information in a monolithic crystal theoretically makes it possible overcome the associated challenge. This requires the deployment of experimental methods, physical simulations, the design of readout microelectronics circuits and original data analysis methods. In addition, the ability to localise interactions in the detector to better than the size of a pixel will help to solve this challenge.

Very high energy gamma ray astronomy observes the sky above a few tens of GeV. This emerging field of astronomy has been in constant expansion since the early 1990s, in particular since the commissioning of the H.E.S.S. array in 2004 in Namibia. IRFU/CEA-Paris Saclay is a particularly active member of this collaboration from the start. It is also involved in the preparation of the future CTAO observatory (Cherenkov Telescope Array Observatory), which is now being installed. The detection of gamma rays above a few tens of GeV makes it possible to study the processes of charged particles acceleration within objects as diverse as supernova remnants or active galactic nuclei. Through this, H.E.S.S. aims in particular at answering the century-old question of the origin of cosmic rays.
H.E.S.S. allows measuring the direction, the energy and the arrival time of each detected photon. The time measurement makes it possible to highlight sources which present significant temporal or periodic flux variations. The study of these variable
Direction de la Recherche Fondamentale
Institut de recherche
sur les lois fondamentales de l’univers

emissions (transient or periodic), either towards the Galactic Center or active nuclei of galaxies (AGN) at cosmological distance allows for a better understanding of the emission processes at work in these sources. It also helps characterizing the medium in which the photons propagate and testing the validity of some fundamental physical laws such as Lorentz invariance. It is possible to probe a wide range of time scales variations in the flux of astrophysical sources. These time scales range from a few seconds (gamma ray bursts, primordial black holes) to a few years (binary systems of high mass, active galaxy nuclei).
One of the major successes of H.E.S.S.s two decades of data-taking. was to conduct surveys of the galactic and extragalactic skies in the very-high energy range. These surveys combine observations dedicated to certain sources, such as the Galactic Center or certain remains of supernovae, as well as blind observations for the discovery of new sources. The thesis subject proposed here concerns an aspect of the study of sources which remains to be explored: the research and study of the variability of very-high energy sources. For variable sources, it is also interesting to correlate the variability in other wavelength ranges. Finally, the source model can help predict its behavior, for example its “high states” or its bursts.

In the coming years, the Euclid mission will provide measurements of the shapes and positions of billions of galaxies with unprecedented precision. As the light from the background galaxies travels through the Universe, it is deflected by the gravity of cosmic structures, distorting the apparent shapes of galaxies. This effect, known as weak lensing, is the most powerful cosmological probe of the next decade, and it can answer some of the biggest questions in cosmology: What are dark matter and dark energy, and how do cosmic structures form?
The standard approach to weak lensing analysis is to fit the two-point statistics of the data, such as the correlation function of the observed galaxy shapes. However, this data compression is sub- optimal and discards large amounts of information. This has led to the development of several approaches based on high-order statistics, such as third moments, wavelet phase harmonics and field-level analyses. These techniques provide more precise constraints on the parameters of the cosmological model (Ajani et al. 2023). However, with their increasing precision, these methods become sensitive to systematic effects that were negligible in the standard two-point statistics analyses.
One of these systematics is source clustering, which refers to the non-uniform distribution of the galaxies observed in weak lensing surveys. Rather than being uniformly distributed, the observed galaxies trace the underlying matter density. This clustering causes a correlation between the lensing signal and the galaxy number density, leading to two effects: (1) it modulates the effective redshift distribution of the galaxies, and (2) it correlates the galaxy shape noise with the lensing signal. Although this effect is negligible for two-point statistics (Krause et al. 2021, Linke et al. 2024), it significantly impacts the results of high-order statistics (Gatti et al. 2023). Therefore, accurate modelling of source clustering is critical to applying these new techniques to Euclid’s weak lensing data.
In this project, we will develop an inference framework to model source clustering and asses its impact on cosmological constraints from high-order statistics. The objectives of the project are:
1. Develop an inference framework that populates dark matter fields with galaxies, accurately modelling the non-uniform distribution of background galaxies in weak lensing surveys.
2. Quantify the source clustering impact on the cosmological parameters from wavelet transforms and field-level analyses.
3. Incorporate source clustering in emulators of the matter distribution to enable accurate data modelling in the high-order statistics analyses.
With these developments, this project will improve the accuracy of cosmological analyses and the realism of the data modelling, making high-order statistics analyses possible for Euclid data.

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-di?erentiation techniques, will be used. Those techniques allow for a very e?cient 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 an reliability and robustness required for precision cosmology.

Galaxy clusters, located at the node of the cosmic web, are the largest gravitationally bound structures in the Universe. Their abundance and spatial distribution are very sensitive to cosmological parameters, such the matter density in the Universe. Galaxy clusters thus constitute a powerful cosmological probe. They have proven to be an efficient probe in the last years (Planck, South Pole Telescope, XXL, etc.) and they are expected to make great progress in the coming years (Euclid, Vera Rubin Observatory, Simons Observatory, CMB- S4, etc.).
The cosmological power of galaxy clusters increases with the size of the redshift (z) range covered by the catalogue. Planck detected the most massive clusters in the Universe in the redshift range 0 Only the experiments studying the cosmic microwave background will be able to observe the hot gas in these first clusters at 2 One thus needs to understand and model the emission of the gas as a function of redshift, but also the emission of radio and infrared galaxies inside the clusters to be ready to detect the first clusters in the Universe. Irfu/DPhP developed the first tools for detecting clusters of galaxies in cosmic microwave background data in the 2000s. These tools have been used successfully on Planck data and on ground-based data, such as the data from the SPT experiment. They are efficient at detecting clusters of galaxies whose emission is dominated by the gas, but their performance is unknown when the emission from radio and infrared galaxies is significant.
This thesis will first study and model the radio and infrared emission from galaxies in the clusters detected in the cosmic microwave background data (Planck, SPT and ACT) as a function of redshift.
Secondly, one will quantify the impact of these emissions on existing cluster detection tools, in the redshift range currently being probed (0 Finally, based on our knowledge of these radio and infrared emissions from galaxies in clusters, we will develop a new cluster extraction tool for high redshift clusters (2 The PhD student will join the Simons Observatory and CMB-S4 collaborations.

The study of the filamentary Cosmic Web is a paramount aspect of modern research in cosmology. With the advent of extremely large and precise cosmological datasets which are now (or within months) coming notably from the Euclid space mission, it becomes feasible to study in detail the formation of cosmic structures through gravitational instability. In particular, fine non-linear aspects of this dynamics can be studied from a theoretical point of view with the hope of detecting signatures in real observations. One of the major difficulty in this regard is probably to make the link between the observed distribution of galaxies along filaments and the underlying matter distribution for which first-principles models are known. Building on recent and state of the art theoretical developments in gravitational perturbation theory and constrained random field theory, the successful candidate will develop first-principles predictions for statistical observables (extrema counts, topological estimators, extrema correlation functions, e.g. Pogosyan et al. 2009, MNRAS 396 or Ayçoberry, Barthelemy, Codis 2024, A&A 686) of the cosmic web, applied to the actual discrete field of galaxies which only traces the total matter in a biased manner. This model will then be applied to the analysis of Euclid data.

The goal of this PhD project is to develop a novel joint analysis for the DESI galaxy clustering
and Planck PR4/ACT CMB lensing data, based on numerical simulations of the surveys and
state-of-the-art machine learning and statistical inference techniques. The aim is to overcome
many of the limitations of the traditional approaches and improve the recovery of cosmological
parameters. The joint galaxy clustering - CMB lensing inference will significantly improve
constraints on the growth of structure upon DESI-only analyses and refine even more the test of general relativity.

The XMM Heritage project on the DEEP Euclid Fornax field aims to characterize distant galaxy clusters by comparing X-ray and optical/IR detections. The two methods call on very different cluster properties; ultimately, their combination will make it possible to set the free parameters of the Euclid cluster selection function over the entire WIDE survey, and thus constitute a fundamental ingredient for Euclid cosmological analysis.

The targeted redshift range ([1-2]) has never been systematically explored, despite being a critical area for the use of clusters in cosmology.
With FornaX, for the first time we'll have access to a large volume at these redshifts, enabling us to statistically quantify the evolution of clusters: role of AGNs in the properties of intracluster gas? Are there massive gas-deficient clusters? What are the respective biases of X-ray and optical detection?
The thesis work will involve (1) building and validating the X-ray cluster catalog; (2) correlating it with the optical/IR catalogs obtained by Euclid; and (3) studying the combined X-ray and optical evolution of the clusters.


All the algorithms for detecting and characterizing clusters in XMM images already exist, but we'll be pushing detection even further by using artificial intelligence techniques (combining spatial and spectral information on sources).
The complex problem of spatial correlation between XMM and Euclid cluster catalogs will also involve AI.

Project website: https://fornax.cosmostat.org/

Gamma-Ray Bursts are short lived (0.1-100 s) gamma-ray transient sources that appear randomly on the entire sky. Even if they have been discovered at the end of the 1960s, their nature remained mysterious until the end of the 1990s. It is only thanks to the observations of the BeppoSAX satellite at the end of the last century and especially thanks to the observations of the Swift satellite starting from 2004, that the mysterious nature of GRBs started to be elucidated.
These emissions are related to the final stages of very massive stars (30-50 times the mass of the Sun) for the long GRBs (2 s) or to the merger of two compact objects (typically two neutron stars) for the short GRBs ( 2s). In either case there is the creation of a powerful relativistic jet, which is at the origin of the electromagnetic emission that is measure in gamma-rays and in other energy bands. If this jet points towards the Earth, GRBs can be detected up to very long distances (z~9.1) corresponding to a young age of the Universe (~500 Myr).
Svom is a sino-french space mission dedicated to GRBs, which has been successfully launched on June 22nd 2024, and in which CEA/Irfu/DAp is deeply involved. The PHD subject is aimed at exploiting the multi-wavelength data of SVOM and its partner telescopes in order to investigate the nature of GRBs, and in particular to make use of X-ray data from the MXT telescope in order to try to constrain the nature of the compact object which is at the origin of the relativistic jets.

Context
Inverse problems, i.e. estimating underlying signals from corrupted observations, are ubiquitous in astrophysics, and our ability to solve them accurately is critical to the scientific interpretation of the data. Examples of such problems include inferring the distribution of dark matter in the Universe from gravitational lensing effects [1], or component separation in radio interferometric imaging [2].

Thanks to recent deep learning advances, and in particular deep generative modeling techniques (e.g. diffusion models), it now becomes not only possible to get an estimate of the solution of these inverse problems, but to perform Uncertainty Quantification by estimating the full Bayesian posterior of the problem, i.e. having access to all possible solutions that would be allowed by the data, but also plausible under prior knowledge.

Our team has in particular been pioneering such Bayesian methods to combine our knowledge of the physics of the problem, in the form of an explicit likelihood term, with data-driven priors implemented as generative models. This physics-constrained approach ensures that solutions remain compatible with the data and prevents “hallucinations” that typically plague most generative AI applications.

However, despite remarkable progress over the last years, several challenges still remain in the aforementioned framework, and most notably:

[Imperfect or distributionally shifted prior data] Building data-driven priors typically requires having access to examples of non corrupted data, which in many cases do not exist (e.g. all astronomical images are observed with noise and some amount of blurring), or might exist but may have distribution shifts compared to the problems we would like to apply this prior to.
This mismatch can bias estimations and lead to incorrect scientific conclusions. Therefore, the adaptation, or calibration, of data-driven priors from incomplete and noisy observations becomes crucial for working with real data in astrophysical applications.

[Efficient sampling of high dimensional posteriors] Even if the likelihood and the data-driven prior are available, correctly sampling from non-convex multimodal probability distributions in such high-dimensions in an efficient way remains a challenging problem. The most effective methods to date rely on diffusion models, but rely on approximations and can be expensive at inference time to reach accurate estimates of the desired posteriors.

The stringent requirements of scientific applications are a powerful driver for improved methodologies, but beyond the astrophysical scientific context motivating this research, these tools also find broad applicability in many other domains, including medical images [3].


PhD project
The candidate will aim to address these limitations of current methodologies, with the overall aim to make uncertainty quantification for large scale inverse problems faster and more accurate.
As a first direction of research, we will extend recent methodology concurrently developed by our team and our Ciela collaborators [4,5], based on Expectation-Maximization, to iteratively learn (or adapt) diffusion-based priors to data observed under some amount of corruption. This strategy has been shown to be effective at correcting for distribution shifts in the prior (and therefore leading to well calibrated posteriors). However, this approach is still expensive as it requires iteratively solving inverse problems and retraining the diffusion models, and is critically dependent on the quality of the inverse problem solver. We will explore several strategies including variational inference and improved inverse problem sampling strategies to address these issues.
As a second (but connected) direction we will focus on the development of general methodologies for sampling complex posteriors (multimodal/complex geometries) of non-linear inverse problems. Specifically we will investigate strategies based on posterior annealing, inspired from diffusion model sampling, applicable in situations with explicit likelihoods and priors.
Finally, we will apply these methodologies to some challenging and high impact inverse problems in astrophysics, in particular in collaboration with our colleagues from the Ciela institute, we will aim to improve source and lens reconstruction of strong gravitational lensing systems.
Publications in top machine learning conferences are expected (NeurIPS, ICML), as well as publications of the applications of these methodologies in astrophysical journals.

References
[1] Benjamin Remy, Francois Lanusse, Niall Jeffrey, Jia Liu, Jean-Luc Starck, Ken Osato, Tim Schrabback, Probabilistic Mass Mapping with Neural Score Estimation, https://www.aanda.org/articles/aa/abs/2023/04/aa43054-22/aa43054-22.html

[2] Tobías I Liaudat, Matthijs Mars, Matthew A Price, Marcelo Pereyra, Marta M Betcke, Jason D McEwen, Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging, RAS Techniques and Instruments, Volume 3, Issue 1, January 2024, Pages 505–534, https://doi.org/10.1093/rasti/rzae030

[3] Zaccharie Ramzi, Benjamin Remy, Francois Lanusse, Jean-Luc Starck, Philippe Ciuciu, Denoising Score-Matching for Uncertainty Quantification in Inverse Problems, https://arxiv.org/abs/2011.08698

[4] François Rozet, Gérôme Andry, François Lanusse, Gilles Louppe, Learning Diffusion Priors from Observations by Expectation Maximization, NeurIPS 2024, https://arxiv.org/abs/2405.13712

[5] Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur, Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems, https://arxiv.org/abs/2407.17667

Context
In 2016, the announcement of the first direct detection of gravitational waves ushered in an era in which the universe will be probed in an unprecedented way. At the same time, the complete success of the LISA Pathfinder mission validated certain technologies selected for the LISA (Laser Interferometer Space Antenna) project. The year 2024 started with the adoption of the LISA mission by the European Space Agency (ESA) and NASA. This unprecedented gravitational wave space observatory will consist of three satellites 2.5 million kilometres apart and will enable the direct detection of gravitational waves at undetectable frequencies by terrestrial interferometers. ESA plans a launch in 2035.
In parallel with the technical aspects, the LISA mission introduces several data analysis challenges that need to be addressed for the mission’s success. The mission needs to prove that with simulations, the scientific community will be able to identify and characterise the detected gravitational wave signals. Data analysis involves various stages, one of which is the rapid analysis pipeline, whose role is to detect new events and characterise the detected events. The last point concerns the rapid estimation of the position in the sky of the source of gravitational wave emission and their characteristic time, such as the coalescence time for a black hole merger.
These analysis tools form the low-latency analysis pipeline. As well as being of interest to LISA, this pipeline also plays a vital role in enabling multi-messenger astronomy, consisting of rapidly monitoring events detected by electromagnetic observations (ground-based or space-based observatories, from radio waves to Gamma rays).


PhD project
The PhD project focuses on the development of event detection and identification tools for the low-latency alert pipeline (LLAP) of LISA. This pipeline will be an essential part of the LISA analysis workflow, providing a rapid detection of massive black hole binaries, as well as a fast and accurate estimation of the sources’ sky localizations as well as coalescence time. These are key information for multi-messager follow-ups as well as for the global analysis of the LISA data.
While rapid analysis methods have been developed for ground-based interferometers, the case of space-based interferometers such as LISA remains a field to be explored. Adapted data processing will have to consider how data is transmitted in packets, making it necessary to detect events from incomplete data. Using data marred by artefacts such as glitches or missing data packages, these methods should enable the detection, discrimination and analysis of various sources: black hole mergers, EMRIs (spiral binaries with extreme mass ratios), bursts and binaries from compact objects. A final and crucial element of complexity is the speed of analysis, which constitutes a strong constraint on the methods to be developed.
To this end, the problems we will be tackling during this thesis will be:
1. The fast parameter inference of the gravitational waves, noticeably, the sky position, and the coalescence time. Two of the main difficulties reside in the multimodality of the posterior probability distribution of the target parameters and the stringent computing time requirements. To that end, we will consider different advanced inference strategies including:
(a) Using gradient-based sampling algorithms like Langevin diffusions or Hamiltonian Monte Carlo methods adapted to LISA’s gravitational wave problem,
(b) Using machine learning-assisted methods to accelerate the sampling (e.g. normalising flows),
(c) Using variational inference techniques.
2. The early detection of black hole mergers.
3. The increasing complexity of LISA data, including, among others, realistic noise, realistic instrument response, glitches, data gaps, and overlapping sources.
4. The online handling of the incoming 5-minute data packages with the developed fast inference framework.
This thesis will be based on applying Bayesian and statistical methods for data analysis and machine learning. However, an effort on the physics part is necessary, both to understand the simulations and the different waveforms considered (with their underlying hypotheses) and to interpret the results regarding the detectability of black hole merger signals in the context of the rapid analysis of LISA data.

Core-collapse supernovae play a crucial role in the stellar evolution of massive stars, the birth of neutron stars and black holes, and the chemical enrichment of galaxies. How do they explode? The explosion mechanism can be revealed by the analysis of multi-messenger signals: the production of neutrinos and gravitational waves is modulated by hydrodynamic instabilities during the second following the formation of a proto-neutron star.
This thesis proposes to use the complementarity of multi-messenger signals, using numerical simulations of the stellar core- collapse and perturbative analysis, in order to extract physical information on the explosion mechanism.
The project will particularly focus on the multi-messenger properties of the stationary shock instability (SASI) and the corotational instability (low T/W) for a rotating progenitor. For each of these instabilities, the signal from different species of neutrinos and the gravitational waves with different polarization will be exploited, as well as the correlation between them.

In little more than two years of scientific operations, JWST has revolutionized our understanding of exoplanets and their atmospheres. The ARIEL space mission, to be launched in 2029, will soon contribute to this revolution. A main finding that has been enabled by the exquisite quality of the JWST data is that exoplanet atmospheres are in chemical disequilibrium. A full treatment of disequilibrium is complex, especially when the atmospheres are metal-rich, i.e. when they contain in significant abundances elements other than hydrogen and helium. In a first step, our project will numerically investigate the extent of chemical disequilibrium in the atmospheres of JWST targets suspected to have metal-rich atmospheres. We will use towards that end an in-house photochemical model. In a second step, our project will explore the effect of super-thermal chemistry as a driver of chemical disequilibrium. This will offer previously-unexplored insight into the chemistry of metal-rich atmospheres, with the potential to shed new light into the chemical and evolutionary paths of low-mass exoplanets.

Planet formation is a key topic of modern astrophysics with implications on existential questions such as the origin of life in the Universe. Quite surprisingly, we do not precisely know when and where planets are formed in protoplanetary disks. Recent observations however indicate that this might happen sooner than we previously believed. But the physical conditions in the young disks remain poorly constrained. During this thesis we propose to test the hypothesis that planets could form early. We will perform 3D simulations of protoplanetary disk formation with gas, dust and including the mechanisms of planetesimal formation. In addition from determining whether planets form early we will be able to predict the architectures of exoplanet systems and to compare them to real ones. This work, beyond the current state-of-the-art, is timely as many efforts are currently being done by our community to better understand exoplanets as well as our origins.

This PhD thesis focuses on developing an advanced analysis framework for inspecting nuclear waste containers using muon tomography, particularly the scattering method. Muon tomography, which leverages naturally occurring muons from cosmic rays to scan dense structures, has proven valuable in areas where traditional imaging methods fail. CEA/Irfu, with expertise in muon detectors, seeks to harness AI and Machine Learning (ML) to optimize muon data analysis, particularly to reduce long exposure times and improve image reliability.

The project will involve familiarizing with muography (muon tomography image) principles, simulating muon interactions with waste containers, and developing ML-based data augmentation and image processing techniques. The outcome should yield efficient tools to interpret muon images, enhance analysis speed, and classify container contents reliably. The thesis aims to improve nuclear waste inspection’s safety and reliability by producing cleaner, faster, and more interpretable muon tomography data through innovative analysis methods.

In agreement with the CERN’s advertised will for the implementation of a super-collider, FCC type, high field superconducting electromagnets, based on Nb3Sn, are being developed. In the framework of the HFM (High Field Magnets) European collaboration, the LEAS at CEA Paris-Saclay is designing, manufacturing, and testing superconducting magnet demonstrators generating up to 16 T. Nb3Sn conductors require a heat treatment at 650 °C. During this heat treatment, several physico-chemical phenomena lead to the formation of the Nb3Sn superconducting phase. These phenomena induce a mechanical state impacting the superconducting properties of the material. A study of the different phenomena inducing dimensional changes inside the conductors would allow estimating the stresses inside the Nb3Sn superconducting phase following the heat treatment. The goal of this thesis is to study, using modeling and experiments, the thermomechanical state of the conductors during the heat treatment in order to estimate the internal stresses and their impact on the superconducting performances. The results will allow the improvement of the Nb3Sn superconducting properties in view of the production of high field magnets for future accelerators.

The interaction of an antiparticle with an atomic nucleus is a type of reaction that needs to be simulated in order to answer fundamental questions. Examples include the PANDA (FAIR) collaboration with antiproton beams of the order of GeV, which plans to study nucleon-hyperon interactions, as well as the neutron skin by producing hyperons and antihyperons. This same neutron skin is also studied with antiprotons at rest in the PUMA experiment (AD - Cern). At the same site, we are collaborating with the ASACUSA experiment to study the production of charged particles. To respond to those studies, our INCL nuclear reaction code has been extended to antiprotons (thesis by D. Zharenov, defended at the end of 2023). Beyond the antiproton there are antideuterons and antiHe-3. These antiparticles are of more recent interest, notably with the GAPS (General AntiParticle Spectrometer) experiment, which aims to measure the fluxes of these particles in cosmic rays. The idea is to highlight dark matter, of which these particles are thought to be decay products, and whose measured quantity should emerge more easily from the astrophysical background noise than in the case of antiprotons. The proposed subject is therefore the implementation of light anti-nuclei in INCL with comparisons to experimental data.

It is proposed to study the salient effects of coupling between discrete and continuous states near various particle emission thresholds using the shell model in the complex energy plane. This model provides the unitary formulation of a standard shell model within the framework of the open quantum system for the description of well bound, weakly bound and unbound nuclear states.
Recent studies have demonstrated the importance of the residual correlation energy of coupling to the states of the continuum for the understanding of eigenstates, their energy and decay modes, in the vicinity of the reaction channels. This residual energy has not yet been studied in detail. The studies of this thesis will deepen our understanding of the structural effects induced by coupling to the continuum and will provide support for experimental studies at GANIL and elsewhere.

The nuclear two-photon, or double-gamma decay is a rare decay mode in atomic nuclei whereby a nucleus in an excited state emits two gamma rays simultaneously. Even-even nuclei with a first excited 0+ state are favorable cases to search for a double-gamma decay branch, since the emission of a single gamma ray is strictly forbidden for 0+ to 0+ transitions by angular momentum conservation. The double-gamma decay still remains a very small decay branch (1E-4) competing with the dominant (first-order) decay modes of atomic internal-conversion electrons (ICE) or internal positron-electron (e+-e-) pair creation (IPC).

The thesis project has two distinct experimental parts: First, we store bare (fully-stripped) ions in their excited 0+ state in the heavy-ion storage ring (ESR) at the GSI facility to search for the double-gamma decay in several nuclides. For neutral atoms the excited 0+ state is a rather short-lived isomeric state with a lifetime of the order of a few tens to hundreds of nanoseconds. At relativistic energies available at GSI, however, all ions are fully stripped of their atomic electrons and decay by ICE emission is hence not possible. If the state of interest is located below the pair creation threshold the IPC process is not possible either. Consequently, bare nuclei are trapped in a long-lived isomeric state, which can only decay by double-gamma emission to the ground state. The decay of the isomers is identified by so-called time-resolved Schottky Mass Spectroscopy. This method allows to distinguish the isomer and the ground state by their (very slightly) different revolution time in the ESR, and to observe the disappearance of the isomer peak in the mass spectrum with a characteristic decay time. Successful experiment establishing the double-gamma decay in several nuclides (72Ge, 98Mo, 98Zr) were already performed and a new experiment has been accepted by the GSI Programme Committee and its realization is planned for 2025.

The second part concerns the direct observation of the emitted photons using gamma-ray spectroscopy. While the storage ring experiments allow to measure the partial lifetime for the double gamma decay, further information on the nuclear properties can be only be achieved by measuring the photon themselves. A test experiment has been performed to study its feasibility and the plans a more detailed study should be developed with the PhD project.

One of the key questions in the field of nuclear structure concerns the emergence of collectivity, and its link with the microscopic structure of the nucleus. Atomic nuclei can exhibit so-called collective behaviours, which means that their constituents, protons and neutrons, move in a coherent way. The main modes of collective nuclear motion are vibrations and rotations. If a nucleus is not deformed, it cannot undergo rotations when excited, but vibrations around its spherical equilibrium shape are possible.
Even-even isotopes of cadmium have been considered textbook examples of vibrational behaviour. However, this interpretation has been questioned following recent experimental studies, which have, with a guidance from theoretical calculations, led to the reorganization of the level schemes of 110,112Cd in terms of rotational excitations, suggesting the presence of a variety of shapes in these nuclei. Thanks to a recent PhD work in our group, this new interpretation has been extended to the 106Cd nucleus. However, questions remain regarding the nature of certain low-lying excited states in this nucleus. In particular, we obtained indications that some excited states may result from a coupling between the so-called octupole (i.e. the nucleus deforms into a pear shape) and quadrupole (i.e. the nucleus oscillates between elongated and flattened shapes) vibrations. To test this hypothesis, a high-precision beta-decay experiment has been proposed at TRIUMF (Vancouver, Canada) using the world's most advanced spectrometer for beta-decay measurements GRIFFIN, to search for weak decay paths in the 106Cd level scheme, and to unambiguously determine the spins of the excited states through the analysis of gamma-gamma angular correlations. Thanks to this measurement it will be possible to solve multiple puzzles concerning the structure of this nucleus, in particular regarding the possible triaxiality of its ground state and the suspected coexistence of multiple shapes.
The student will be in charge of the analysis of this experiment, which will take place in 2025. Then, based on the results of this analysis, they will proceed to a re-evaluation of the population cross sections of excited levels in 106Cd, which were measured with the new generation gamma-ray spectrometer AGATA at GANIL using the Coulomb excitation technique. From this combination of measurements, we hope to obtain, for the first time in the nuclear chart, the complete set of transition probabilities between the states resulting from the coupling between octupole and quadrupole vibrations. We will then proceed to the interpretation of the results in close collaboration with experts in nuclear-structure theory.
This thesis work will make it possible for the student to follow a research project in its entirety, from the preparation of the experiment to its theoretical interpretation, and to become familiar with several experimental gamma-ray spectroscopy techniques, using the most advanced gamma-ray spectrometers in the world.

Protons and neutrons are made of partons (quarks and gluons) that interact via the strong force, governed by Quantum Chromodynamics (QCD). While QCD can be computed at high energies, its complexity reveals itself at low energies, requiring experimental inputs to understand nucleon properties like their mass and spin. The experimental extraction of the Generalized Parton Distributions (GPDs), which describe the correlation of the partons longitudinal momenta and transverse positions within nucleons, provide critical insights into these fundamental properties.
This thesis focuses on analyzing data from the CLAS12 detector, an experiment part of Jefferson Lab's research infrastructure, one the 17 National Laboratory in the USA. CLAS12, a 15-meter-long fixed-target detector with large acceptance, is dedicated to hadronic physics, particularly GPDs extraction. The selected student will study the exclusive photoproduction of the phi meson (gamma p->phi p’), which is sensitive to gluon GPDs, still largely unexplored. The student will develop a framework to study this reaction in the leptonic decay channel (phi -> e+e-) and develop a novel Graph Neural Network-based algorithm to enhance the scattered proton detection efficiency.
The thesis will aim at extracting the cross section of the photoproduction of the phi, and interpret it in term of the proton's internal mass distribution. Hosted at the Laboratory of Nucleon Structure (LSN) at CEA/Irfu in Saclay, this project involves international collaboration within the CLAS collaboration, travel to Jefferson Lab for data collection, and presentations at conferences. Proficiency in particle physics, programming (C++/Python), and English is required. Basic knowledge of particle detectors and Mahine Learning is advantageous but not mandatory.

One of the strongest research projects in recent years has emerged from a critical, unresolved question about the natural origin of nuclei heavier than iron. The closed neutron shell, N = 126, as the final waiting point in the r-process (rapid neutron capture process), plays an essential role in the formation of these nuclei. However, recent efforts to synthesize superheavy elements and explore N = 126 neutron-rich nuclei have faced significant challenges due to extremely low cross sections using traditional fusion-evaporation reactions.
These factors highlight the urgent need for alternative reaction mechanisms. One alternative has been identified in multinucleon transfer (MNT) reactions, which offer a promising route to neutron-rich heavy nuclei. The challenge is to isolate the desired nuclei from the multitude of products generated during the reaction.
We have been working on this reaction mechanism for several years, performing experiments at Argonne National Laboratory and other international laboratories.
The aim of this thesis is to analyse the data collected during the Argonne experiment (end 2023) and to propose a new experiment at the spectrometer Prisma (Legnaro National Lab) coupled with the Agata germanium detector.

The fission process involves the violent splitting of a heavy nucleus into two fission fragments, resulting in over 300 different isotopes. Understanding the distribution and production of these fragments, known as fission yields, is essential for grasping the underlying mechanisms of fission, which are influenced by nuclear structure and dynamics. Accurate measurements of fission yields are crucial for advancing nuclear energy applications, particularly in developing Generation IV reactors and recycling spent nuclear fuel. The VAMOS magnetic spectrometer enables precise fission yield measurements due to its large acceptance and identification capabilities for various isotopes. An experimental campaign at VAMOS in 2024 utilized beams of \(^{238}\)U and \(^{232}\)Th on a carbon target to produce fissioning actinides. The combination of VAMOS with a new Silicon telescope (PISTA) enhances data quality significantly. The candidate will analyze VAMOS data to produce high-resolution fission yields and study uncerta

The Matter’s Origin from RadioActivity (MORA) experiment searches for a sign of CP violation in nuclear beta decay, via the precise measurement of the so-called D correlation. An innovative technique of in-trap ion polarization for such a measurement enables attaining unprecedented sensitivity to New Physics, which could explain the matter-antimatter asymmetry observed in the universe. With a goal in sensitivity on a non-zero D of a few 10-4, the measurement that MORA is undertaking at Jyväskylä will be competitive with the best limit obtained so far on a non-zero D correlation in neutron decay [5]. To attain such precision regime several weeks of data taking are required along the coming years (2025-2027) at Jyväskylä, both for 23Mg+ and 39Ca+. The data analysis has to be undertaken in parallel. Crosschecks and adaptation of existing simulations of individual detectors of MORA, performed with GEANT4 and PENELOPE Monte Carlo codes, are required to pursue the investigation of systematics effects potentially affecting the final sensitivity on D. Dissemination of the results of the data analysis at national and international conferences will be asked to the PhD student.

Targeted Alpha Therapy (TAT) is a promising new method of treating cancer. It uses radioactive substances called alpha-emitting radioisotopes that are injected into the patients body. These substances specifically target cancer cells, allowing the radiation to be concentrated where it is needed most, close to the tumors. Alpha particles are particularly effective because of their short range and ability to target and destroy cancer cells.
As with any new treatment, TAT must undergo preclinical studies to test its effectiveness and compare it to other existing treatments. Much of this research is done in laboratory, where cancer cells are exposed to these radioactive substances to observe their effects, such as cell survival. However, assessing the effects of alpha particles requires special methods because they behave differently than other types of radiation.
Recently, a method for measuring the radiation dose received by cells in laboratory experiments has been successfully tested. This method uses detecto

Heavy-ion collisions provide a unique opportunity to study the quark-gluon plasma (QGP), an exotic state of matter where quarks and gluons are no longer confined within hadrons and believed to have existed just a few microseconds after the Big Bang. Charm quarks are among the key probes for investigating the QGP. Indeed, they retain information about their interactions with the QGP, making them essential for understanding the properties of the plasma. The production of charm quarks and their interactions with the QGP is studied through the measurements of hadrons, mesons and baryons, containing at least one charm quark or antiquark, like D0 mesons or Lambda_c baryons. However, the hadronization process—how charm quarks become confined within colorless baryons or mesons—remains poorly understood.

A promising approach to gaining deeper insights into charm hadronization is to measure the elliptic flow of charm hadrons, which refers to long-range angular correlations and is a signature of collective effects due to thermalization. By comparing the elliptic flow of D0 mesons and Lambda_c baryons, researchers can better understand the charm hadronization mechanism, which is sensitive to the properties of the created medium.

To measure elliptic flow, the selected student will develop an innovative method that leverages the full capabilities of the detector. This method, which has never been applied before, provides a more intuitive and theoretically sound interpretation of the results. The candidate will adapt this technique for use with the LHCb detector to measure, compare, and interpret the elliptic flow of Lambda_c charm baryons and D0 mesons with the PbPb samples collected by LHCb in 2024.

One of the main activities in nuclear physics is the study of the properties of the exotic nuclei up to the limits of the nuclear chart, in regions with extreme proton-neutron ratios (proton/neutron driplines) and at the highest masses A and atomic numbers Z. The so-called super-heavy nuclei (SHN) are expected to exist beyond the liquid drop limit of existence defined by a vanishing fission barrier, thanks to the quantum mechanical shell effects. These nuclei are particularly interesting because they are at the limit between few-body and large n-body physics: the magic proton and neutron numbers, Z and N, are replaced by a magic region or island extended in Z and N.

The synthesis of these very and super-heavy nuclei by fusion-evaporation reactions is an experimental challenge due to the extremely low cross-sections. Modelling the complete reaction in order to guide the experiments is also a difficult challenge, as models developed for lighter nuclei cannot simply be extrapolated. Fusion reactions are hindered compared to what is observed with light nuclei, because the very strong Coulomb interaction is enhanced by the strong repulsion caused by the large number of positive charges (protons) in the system in competition with the attractive strong (nuclear) force in a highly dynamic regime. The predictive power of the models needs to be improved, although the origin of the hindrance phenomenon is qualitatively well understood. The quantitative ambiguities are large enough to observe a few orders of magnitude differences in the fusion probabilities calculated by different models. A small change in the cross-section could result in many months being required to perform successful experiments.

At GANIL, in collaboration with other institutes, we have developed a model that describes all the three steps of the reaction to synthesise super-heavy nuclei. Future developments will focus on finding ways to assess the models in order to improve their predictive power, including the design of dedicated experiments to constrain the so-called fusion hindrance. Of course, a careful uncertainty analysis, which is new in theoretical nuclear physics, will be necessary to assess the different ideas. Standard methods as well as state-of-the-art data analysis methods such as Bayesian analysis may be used.

This PhD work will be done in collaboration with the experimental group at GANIL and a research team in Warsaw (Poland). Depending on the skills of the student, the thesis will be more oriented towards formal developments or towards the experiments at the new S3 facility at Spiral2. Participation in experiments is possible.

Neutrinoless double beta decay (0nßß) represents a pivotal area of research in nuclear physics, offering profound insights into neutrino properties and the potential violation of lepton number conservation. The CUPID experiment is at the forefront of this investigation, employing advanced scintillating bolometers at cryogenic temperatures to minimize radioactive background noise. It aims to achieve unprecedented sensitivity in detecting 0nßß decay using lithium molybdate (Li2MoO4) crystals. These crystals are particularly advantageous due to their scintillation properties and the high Q-value of the decay process, which lies above most environmental gamma backgrounds. In turn this endeavour will require operating a fine grained array of 1596 dual heat/light detectors with excellent energy resolution. The proposed thesis integrates artificial intelligence (AI) techniques to enhance data analysis, reconstruction, and modeling for the CUPID experiment demonstrators and the science exploitation of CUPID.

The thesis will focus on two primary objectives:
1. Improved Time Series Event Reconstruction Techniques
- CNN based denoising and comparison against optimal classical techniques
2. Multivariate science analysis of a large neutrino detector array
- Analysis of Excited States: The study will use Geant4 simulations together with the CUPID background model as training data to optimize the event classification and hence science potential for the analysis of 2nßß decay to excited states.

Neutrinos are promising messengers for detecting physics beyond the Standard Model. Their elusive nature and unexplained mass suggest they could open new pathways for physics. Neutrino oscillation research has entered a precision era with experiments like T2K, which in 2020 observed hints of CP violation in the leptonic sector that could shed light on the question of matter-antimatter asymmetry in the Universe.

The T2K experiment, located in Japan, studies neutrino oscillations by generating an intense beam of muon neutrinos (and anti-neutrinos). This beam is measured at two locations: a near detector, designed to reduce systematic uncertainties related to the neutrino flux and interaction models, and a far detector (Super-Kamiokande), tasked with measuring the disappearance of muon neutrinos and the appearance of electron neutrinos after oscillation.
In 2023, T2K entered its second phase with increased beam power and upgrade of the near detector, including a highly granular new target and High-Angle Time Projection Chambers (HA-TPC). These improvements enable more precise reconstruction of particles produced by neutrino interactions.

IRFU teams contributed by developing HA-TPCs equipped with resistive Micromegas technology. This work improves spatial resolution and the precision of particle momentum. The thesis explores optimizing the particle track reconstruction algorithms in the HA-TPCs using advanced techniques, as well as analyzing T2K data with the upgraded ND280 to achieve a 3 sigma level of significance for CP violation. T2K is thus paving the way for future experiments like DUNE and Hyper-Kamiokande, opening new perspectives for the next two decades.

The synthesis and study of the superheavy nuclei (SHN) is still one of the major challenges of modern nuclear physics. Experimental studies of hitherto unknown nuclei depend crucially on their identification in terms of atomic charge Z and nuclear mass A. To complete particle ID capabilities of the separator-spectrometer set-up S3 at GANIL-SPIRAL2, already providing a mass resolution sufficient to resolve the A of SHN, its focal plane detection system SIRIUS will be provided with X-ray detection for Z identification of the species of interest. The development of an X-ray detection system array, employing thin germanium crystals with thin entrance windows (based on so-called Low-Energy Photon Spectrometers (LEPS)), its integration in the SIRIUS set-up as well as its in-beam test and use for SHN decay spectroscopy will be the main tasks of the Ph.D. thesis. The Ph.D. student will be involved in SHN spectroscopic studies at GANIL and international accelerator laboratories like ANL, which serve as efficient preparation of the experiment campaigns planned at S3 which is scheduled to come online in 2024. This Ph.D. thesis work is an important ingredient for the preparation of the detection instrumentation needed for the S3 operation.

The objective of the thesis is a precise measurement of the mass and width of the W boson, by studying its leptonic decays with the ATLAS detector at the LHC. The analysis will be based on data from Run 2 of the LHC, and aims for an precision on the mass of 10 MeV.

The candidate will be involved in the study of the alignment and calibration of the ATLAS muon spectrometer. IRFU played a leading role in the design and construction of this instrument and is heavily involved in its scientific exploitation. This will involve optimally combining the measurement given by the spectrometer with that of the ATLAS inner detector, using a precise model of the magnetic field and the relative positioning of these systems, in order to reconstruct the muon kinematics with the precision required for measurement.

The second phase of the project consists of improving the modeling of the W-boson production and decay process and optimizing the analysis itself in order to minimize the final uncertainty of the measurement. The measurement result will be combined with other existing measurements, and interpreted in terms of compatibility with the Standard Model prediction or as an indication of the presence of new physics.

Positron emission tomography (PET) is a nuclear medical imaging technique widely used in oncology and neurobiology.
We're proposing you to contribute to the development of an ambitious, patented technology: ClearMind. This gamma photon detector uses a monolithic PbWO4 crystal, in which Cherenkov and scintillation photons are produced. These optical photons are converted into electrons by a photoelectric layer and multiplied in a MicroChannel plate. The induced electrical signals are amplified by gigahertz amplifiers and digitized by SAMPIC fast acquisition modules. The opposite side of the crystal will be fitted with a matrix of silicon photomultiplier (SiPM).

You will work in an advanced instrumentation laboratory in a particle physics environment .
The first step will be to optimize the "components" of ClearMind detectors, in order to achieve nominal performance. We'll be working on scintillating crystals, optical interfaces, photoelectric layers and associated fast photodetectors, and readout electronics.
We will then characterize the performance of the prototype detectors on our measurement benches.
The data acquired will be interpreted using in-house analysis software written in C++ and/or Python.
Finally, we will compare the physical behavior of our detectors to Monté-Carlo simulation software (Geant4/Gate).
A particular effort will be devoted to the development of ultra-fast scintillating crystals in the context of a European collaboration.

The proposed thesis project focuses on studying neutrino oscillations, a key quantum phenomenon for exploring New Physics beyond the Standard Model. These oscillations, compared between neutrinos and antineutrinos, could shed light on one of the most fundamental questions in particle physics: the origin of the matter-antimatter asymmetry in the Universe.

The T2K experiment, located in Japan, studies these oscillations by generating an intense beam of muon neutrinos (and antineutrinos). This beam is measured at two points: a near detector, used to reduce systematic uncertainties related to the neutrino flux and interaction models, and a far detector (Super-Kamiokande), responsible for measuring the disappearance of muon neutrinos and the appearance of electron neutrinos after oscillations.

The thesis project is divided into two parts. The first part will involve calibrating the new detectors (new time projection chambers using resistive MicroMegas technology) to measure the neutrino energy spectrum and assess the associated systematic uncertainties. The second part will focus on analyzing the newly collected data, allowing for more precise measurements of oscillation parameters, improving the understanding of neutrino-nucleus interactions, and measuring CP violation in neutrino oscillations with 3 sigma significance in the case of maximal violation, as indicated by the latest T2K results, and ultimately 5 sigma in the future Hyper-Kamiokande experiment, which will use the same beam and near detector as T2K.

Since the discovery of the Higgs boson (H) in 2012 by the ATLAS and CMS experiments, and after more than 10 years of studying its properties, especially thanks to the large Run 2 datasets from the LHC collected by both collaborations between 2015 and 2018, everything seems to indicate that we have finally completed the Standard Model (SM), as it was predicted sixty years ago. However, despite the success of this theory, many questions remain unanswered, and in-depth studies of the scalar sector of the SM could provide us with hints about how to address them.

The study of double Higgs boson (HH) production is currently of particular interest to the high-energy physics community, as it constitutes the best experimental handle to access the H self coupling, and consequently the Higgs potential V(H). Due to its direct links with the electroweak phase transition (EWPT), the shape of V(H) is particularly relevant for beyond the Standard Model (BSM) theories that attempt, for instance, to explain primordial baryogenesis and the matter-antimatter asymmetry in our universe. Some of these models predict an expanded scalar sector, involving the existence of additional Higgs bosons, often interacting preferentially with the SM Higgs.

The CMS group at CEA-Saclay/IRFU/DPhP therefore wishes to offer a PhD position focused on the search for resonant HH production, concentrating on the H(bb)H(tautau) channel, with the aim of constraining these models, for the first time involving a complete characterization of the BSM signal and its interferences with the SM. The selected student would participate in well-established research activities within the CMS collaboration and the CEA group, in connection with several institutes in France and abroad.

This proposal focuses on enhancing tracking performance for the LHCb experiments during Run 5 at the Large Hadron Collider (LHC) through the exploration of various machine learning-based algorithms. The Upstream Tracker (UT) sub-detector, a crucial component of the LHCb tracking system, plays a vital role in reducing the fake track rate by filtering out incorrectly reconstructed tracks early in the reconstruction process. As the LHCb detector investigates rare particle decays, studies CP violation in the Standard Model, and study the Quark-Gluon plasma in PbPb collisions, precise tracking becomes increasingly important.

With upcoming upgrades planned for 2035 and the anticipated increase in data rates, traditional tracking methods may struggle to meet the computational demands, especially in nucleus-nucleus collisions where thousands of particles are produced. Our project will investigate a range of machine learning techniques, including those already demonstrated in the LHCb’s Vertex Locator (VELO), to enhance the tracking performance of the UT. By applying diverse methods, we aim to improve early-stage track reconstruction, increase efficiency, and decrease the fake track rate. Among these techniques, Graph Neural Networks (GNNs) are a particularly promising option, as they can exploit spatial and temporal correlations in detector hits to improve tracking accuracy and reduce computational burdens.

This exploration of new methods will involve development work tailored to the specific hardware selected for deployment, whether it be GPUs, CPUs, or FPGAs, all part of the futur LHCb’s data architecture. We will benchmark these algorithms against current tracking methods to quantify improvements in performance, scalability, and computational efficiency. Additionally, we plan to integrate the most effective algorithms into the LHCb software framework to ensure compatibility with existing data pipelines.

Future experiments on linear colliders (e+e-) with low hadronic background require improvements in the spatial resolution of pixel vertex detectors to the micron range, in order to determine precisely the primary and secondary vertices for particles with a high transverse momentum. This kind of detector is set closest to the interaction point. This will provide the opportunity to make precision lifetime measurements of short-lived charged particles. We need to develop pixels arrays with a pixel dimension below the micron squared. The proposed technologies (DOTPIX: Quantum Dot Pixels) should give a significant advance in particle tracking and vertexing. Although the principle of these new devices has been already been studied in IRFU (see reference), this doctoral work should focus on the study of real devices which should then be fabricated using nanotechnologies in collaboration with other Institutes. This should require the use of simulation codes and the fabrication of test structures. Applications outside basics physics are X ray imaging and optimum resolution sensors for visible light holographic cameras.

Recent developments have recognized that quantum causal structures introduce a new non-classical resource known as causal indefiniteness, opening up novel perspectives in quantum information. Despite theoretical advancements and several experimental realizations, the conceptual implications of indefinite causality remain poorly understood. Concurrently, quantum causality has emerged as a crucial foundation for elucidating the discrepancies between operational approaches and spacetime physics. It has already facilitated a novel or enhanced understanding of fundamental concepts such as events (Vilasini and Renner, Phys. Rev. Lett. 133, 080201), facts (Brukner, Nature Phys. 16, 1172–1174, 2020), inputs/outputs (Chiribella and Liu, Comm. Phys. 5, 190, 2022), systems (Grinbaum, Stud. Hist. Phil. Mod. Phys. 58, 22-30, 2017), and computation (Araujo et al., Phys. Rev. A 96, 052315, 2017).
In this PhD project, the candidate will develop a systematic understanding of the conceptual lessons of indefinite causality within the classical, quantum, and generalized probabilistic theory (GPT) frameworks. They will examine the foundational significance of bipartite and multipartite settings, including their spatiotemporal and computational capacities. To make significant progress in quantum foundations, the candidate will seek to extract insights from indefinite causality to deepen our understanding of standard quantum theory, quantum information, and quantum interpretations.
Specific research questions include:
• Establishing conceptual grounds for the identification of systems and events across time, particularly in relation to indefinite causal orders and to "Wigner's friend" scenarios.
• Placing this emerging foundational discussion within a broader philosophical and metaphysical framework.
• Addressing the notion of the agent/observer as a theoretical rather than a metatheoretical entity.
Publications are expected in physics journals (PRL, PRA, NJP, Quantum) and/or philosophy of physics journals (Philosophy of physics, BJPS, Found. Phys., SHPMP). Collaborations are expected with groups in France, Austria, Belgium, and Canada.