VHEE Radiotherapy with Electron Beams from a Laser-Plasma Accelerator
The research programs conducted at the Lasers Interations and Dynamics Laboratory of the French Atomic Energy Commission (CEA) aim to understand the fundamental processes involved in light-matter interactions and their applications. As part of the CEA-LIDYL, the Physics at High Intensity (PHI) group conducts studies of laser-matter interactions at extreme intensities, for which matter turns into an ultra-relativistic plasma. Using theory, simulations and experiments, researchers develop and test new concepts to control the laser-plasma interaction with the aim of producing novel relativistic electron and X-UV attosecond light sources, with potential applications to fundamental research, medicine and industry.
In collaboration with the Lawrence Berkeley National Laboratory, the group strongly contributes to the development of the code WarpX used for the high-fidelity modelling of laser-maIer interactuons. It also pioneered the study and control of remarkable optical components called ‘plasma mirrors’, which can be obtained by focusing a high-power laser with high contrast on an initially solid target. In the past five years, the PHI group has developed core concepts exploiting plasma mirrors to manipulate extreme light for pushing the frontiers of high-field Science. One of these concepts uses plasma mirrors as high-charge injectors to level up the charge produced in laser-plasma accelerators (LPAs) to enable their use for medical studies such very high energy electrons (VHEE) radiotherapy. This concept is being implemented at CEA on the UHI100 100 TW laser facility in 2025 to deliver 100 MeV - 200 MeV electron beams with 100 pC charge/bunch for the study of high-dose rate deposition of VHEE electrons on biological samples.
In this context, the PhD candidate will use our simulation tool WarpX to optimize the properties of the electron beam produced by LPAs for VHEE studies (electron beam quality and final energy). He/She will then study how the LPA electron beam deposits its energy in water samples (as biological medium) using Geant4. This will help assessing dose deposition at ultra-high dose rate and develop novel dosimetry techniques for VHEE LPA electron beams. Finally, the Reactive Oxygen Species (ROS) production and fate in water will be studied using the Geant4-DNA toolkit. This module has mainly data tabulated at electron energies below 10 MeV and will therefore require measures cross-section of water-ionization processes from experiments at 100 MeV. This will be performed on the UHI100 100 TW laser by the DICO group of the CEA-LIDYL, in collaboration with the PHI group.
Quantum simulation of atomic nulei
Atomic nuclei constitute strongly correlated quantum many-body systems governed by the strong interaction of QCD. The nuclear shell model, which diagonalizes the Hamiltonian in a basis whose dimension grows exponentially with the number of nucleons, represents a well-established approach for describing their structure. However, this combinatorial explosion confines classical high-performance computing to a restricted fraction of the nuclear chart.
Quantum computers offer a promising alternative through their natural ability to manipulate exponentially large Hilbert spaces. Although we remain in the NISQ era with its noisy qubits, they could revolutionize shell model applications.
This thesis aims to develop a comprehensive approach for quantum simulation of complex nuclear systems. A crucial first milestone involves creating a software interface that integrates nuclear structure data (nucleonic orbitals, nuclear interactions) with quantum computing platforms, thereby facilitating future applications in nuclear physics.
The project explores two classes of algorithms: variational and non-variational approaches. For the former, the expressivity of quantum ansätze will be systematically analyzed, particularly in the context of symmetry breaking and restoration. Variational Quantum Eigensolvers (VQE), especially promising for Hamiltonian-based systems, will be implemented with emphasis on the ADAPT-VQE technique tailored to the nuclear many-body problem.
A major challenge lies in accessing excited states, which are as crucial as the ground state in nuclear structure, while VQE primarily focuses on the latter. The thesis will therefore develop quantum algorithms dedicated to excited states, testing various methods: Hilbert space expansion (Quantum Krylov), response function techniques (quantum equations of motion), and phase estimation-based methods. The ultimate objective is to identify the most suitable approaches in terms of scalability and noise resilience for applications with realistic nuclear Hamiltonians.
Modeling and prediction of electromagnetic emissions from power converters using deep learning
In recent years, electromagnetic compatibility (EMC) in power converters based on wide bandgap (WBG) semiconductors has attracted growing interest, due to the high switching speeds and increased frequencies they enable. While these devices improve power density and system efficiency, they also generate more complex conducted and radiated emissions that are challenging to control. In this context, this thesis focuses on the prediction, modeling, and characterization of electromagnetic interference (EMI) (> 30 MHz), both conducted and radiated, in high-frequency power electronic systems. The work is based on a multi-subsystem partitioning method and an iterative co-simulation approach, combined with in situ characterization to capture non-ideal and nonlinear phenomena. In addition, deep learning techniques are employed to model EMI behavior using both measured and simulated data. Generative artificial intelligence (Generative AI) is also leveraged to automatically generate representative and diverse configurations commonly encountered in power electronics, thereby enabling efficient exploration of a wide range of EMI scenarios. This hybrid approach aims to enhance analysis accuracy while accelerating simulation and design phases.
Towards real-time simulation of thermal scenes in a tokamak to support plasma operations.
Monitoring the surface temperatures and heat fluxes of the walls in nuclear fusion devices is crucial for the operation of fusion machines. To ensure the reliability of these measurements, particularly through infrared imaging, CEA is developing a digital twin capable of modeling the entire infrared (IR) measurement chain, from the thermal source to the sensor.
The objective of this thesis is to create a thermal model that can predict heat fluxes and surface temperatures across the entire machine wall, with a goal of real-time computation. This approach is based on two key developments:
1)Development of a Monte Carlo statistical method: This method will solve the heat equation over large geometries in a complex environment, including a variety of heat sources and materials.
2)Acceleration of calculations on graphics processing units (GPU): Utilization of the Kokkos environment to optimize calculation performance while ensuring portability across all high-performance computing (HPC) platforms.
These developments will be validated and quantitatively evaluated on two experimental platforms: the laboratory test bench MAGRYT and the WEST tokamak, used as a demonstrator machine. The thesis will be conducted in a collaborative framework between CEA/DRF/IRFM and CEA/DES/ISAS. The developments will be integrated into the IR digital twin developed by CEA/IRFM for fusion machines and within a dedicated ray-tracing application for CEA/DES.
Modelling/Simulation of the synthesis of anti-corrosion coatings using the MOCVD process for low-carbon energy production
The durability of materials used in many areas of energy production is limited by their degradation in the operating environment, which is often oxidising and at high temperature. This is particularly true of High Temperature Electrolysers (HTE) for the production of ‘green’ hydrogen, or the fuel cladding used in nuclear reactors to produce electricity. Anti-corrosion coatings can/should be applied to improve the lifespan of these installations, thereby conserving resources. A process for synthesising coatings using a reactive vapour route with liquid organometallic precursors (DLI - MOCVD) appears to be a very promising process.
The aim of this thesis is to model and simulate the DLI-MOCVD coating synthesis process for the two applications proposed above. Simulation results (deposition rate, deposit composition, spatial homogeneity) will be compared with experimental results from large-scale ‘pilot’ reactors at the CEA in order to optimise the model's input parameters. On the basis of this CFD simulation/experiments dialogue, the optimum conditions for deposition on a scale 1 component will be proposed. A coupling between CFD simulations and Machine Learning will be developed to accelerate the change of scale and the optimisation of scale 1 deposits.
From Combustion to Astrophysics: Exascale Simulations of Fluid/Particle Flows
This thesis focuses on the development of advanced numerical methods to simulate fluid-particle interactions in complex environments. These methods, initially used in industrial applications such as combustion and multiphase flows, will be enhanced for integration into simulation codes for exascale supercomputers and adapted to meet the needs of astrophysics. The objective is to enable the study of astrophysical phenomena such as the dynamics of dust in protoplanetary disks and the structuring of dust in protostars and the interstellar medium. The expected outcomes include a better understanding of planetary formation mechanisms and disk structuring, as well as advancements in numerical methods that will benefit both industrial and astrophysical sciences.
Topologic optimization of µLED's optical performance
The performance of micro-LEDs (µLEDs) is crucial for micro-displays, a field of expertise at the LITE laboratory within CEA-LETI. However, simulating these components is complex and computationally expensive due to the incoherent nature of light sources and the involved geometries. This limits the ability to effectively explore multi-parameter design spaces.
This thesis proposes to develop an innovative finite element method to accelerate simulations and enable the use of topological optimization. The goal is to produce non-intuitive designs that maximize performance while respecting industrial constraints.
The work is divided into two phases:
Develop a fast and reliable simulation method by incorporating appropriate physical approximations for incoherent sources and significantly reducing computation times.
Design a robust topological optimization framework that includes fabrication constraints to generate immediately realizable designs.
The expected results include optimized designs for micro-displays with enhanced performance and a methodology that can be applied to other photonic devices.
Control of trapped electron mode turbulence with an electron cyclotron resonant source
The performance of a tokamak plasma largely depends on to the level of turbulent transport. Trapped electron modes are one of the main instabilities responsible for turbulence in tokamaks. On the other hand, electron cyclotron resonance heating is a generic heating system for tokamaks. Both physical processes rely on resonant interactions with electrons. Non-linear interaction between the resonant processes is theoretically possible. This thesis aims to evaluate the possibility of exploiting this non-linear interaction to stabilize the trapped electron modes instability within tokamak plasmas, using a heating source present on many tokamaks, including ITER. This control technique could improve the performance of certain tokamaks without any extra cost.
The thesis will be based on a theoretical understanding of the two processes studied, will require the use of the gyrokinetic code GYSELA to model the non-linear interactions between resonant processes, and will include an experimental aspect to validate the identified turbulence control mechanism.
Development of algorithms and modeling tools of Low-Energy Critical Dimension Small Angle X-ray Scattering
This PhD will take place at the CEA–LETI, a major European actor in the semiconductor industry, and more precisely, at the Nanocharacterization platform of the CEA–LETI witch offer world-class analytical techniques and state-of-the-art instruments. Our team aims to accompany the industry in the development of new characterization tools and so to meet the metrological needs of future technological nodes. Over the past few years, pioneer developments on a new metrology technique based on hard x-ray scattering called CD-SAXS were done at the PFNC. This technique is used to reconstruct the in-plane and out-of-plane structure of nanostructured thin-films with a sub-nm resolution. In this project, we are looking to extend the CD-SAXS approach leveraging the recent breakthrough in the development of low-energy x-ray sources (A. Lhuillier et al. 1988, Nobel prize 2023) called High Harmonics Generation (HHG) sources. Therefore, you will participate in the development of a new and promising characterization methods called Low-energy critical dimension small angle x-ray scattering. The very first proof of concept of this new measurement was conducted in November 2023.
Mission:
In order to include in the data reduction the measurement specificities of this new approach (multi-wavelength, low energy, …) your mission will focus on several aspects to explore in parallel:
- Develop new modeling tools to analyze the data:
o Finite element simulations with Maxwell solver
o Analytical Fourier Transform (similar to standard CD-SAXS) vs dynamical theory
o Comparison between the two approaches
- Build new models dedicated to lithography problematic (CD, overlay, roughness)
- Define the limitations of the technique through the simulation (in term of resolution (nm), uncertainty)
This work will support the development of CD-SAXS measurements with a laboratory HHG (High Harmonic Generation) source lead by a Postdoctoral fellow.