AI : modelisation and scaling in laborator astrophysics
In astrophysics, accreting systems produce X-ray sources commonly observed by satellites and ground
based telescopes. Spectral signatures allow us to deduce the mass, magnetic field, accretion rate, and
chemical composition of the star and structures. However, these structures are found in very small spatial
areas and are not resolved by observational tools. Laboratory astrophysics allows us to miniaturize these
processes and study them through experiments using high-power lasers. These experiments allow for the
characterization of the plasma and its spatial structuring.
The postdoctoral fellow will exploit the possibilities of using physically informed neural networks to study the possibility of extrapolating radiative hydrodynamic simulation results. He will develop a tool to simply determine the relevant materials and regimes for sizing laboratory experiments. Finally, he will use AI to try to find scaling law relationships between two systems.
Particle-in-cell modeling of elastic collisions in dense and cold plasmas with applications to ultrafast beam-plasma and laser-plasma interactions
The particle-in-cell (PIC) method is widely employed to simulate the kinetics of plasmas subjected to intense laser or particle beams. Modern PIC codes now routinely include additional modules describing atomic physics processes, but their accuracy is questionable in relatively cold (at temperatures below a few tens of eV) and dense (close to the density of a solid) media.
This postdoctoral project aims to improve the treatment of elastic collisions in PIC simulations by drawing on transport theories derived for liquid metals and dense plasmas, i.e. by taking into account electronic degeneracy, electronic screening and atomic ordering effects. This model will be implemented into the PIC CALDER code developed at CEA. Once validated, this new model will be used in PIC simulations to examine its influence in setups involving solid targets exposed to ultraintense and ultrashort electron or laser beams.
Excited electronic states in the GW Approximation coupled to the Projector Augmented-Wave Approach
This project aims to address a major gap in ab initio calculations by enabling reliable simulations of excited electronic states (GW method) using the Projector Augmented-Wave (PAW) approach. These advances will be integrated into the open-source software ABINIT, a recognized international collaborative project. The GW approximation is considered the gold standard for determining electronic energy levels in condensed matter, correcting the underestimated band gap in DFT. The PAW method, on the other hand, offers precision and flexibility and is widely used for ground state and material response calculations.
However, the combined GW+PAW approach encounters difficulties in some well-identified cases (e.g., zinc oxide), with underlying reasons understood but not yet fully resolved. Low-energy excited states are well described, but high-energy states remain problematic. The current debate focuses on the need to perform complete (but computationally expensive) calculations, to neglect certain terms (with complex error control), or to modify the PAW method (at the cost of reduced efficiency).
The project aims to adapt the PAW formalism to the GW approach, to develop a fast and accurate numerical scheme, and to clarify the current, somewhat confusing situation. The CEA team is a leading developer of ABINIT for PAW and GW and will ensure access to large computing resources. The postdoctoral objectives include theoretical development, implementation in ABINIT, and improving electronic properties for realistic solid systems (surfaces, semiconductor junctions, etc.).
Dimensionality reduction and meta-modelling in the field of atmospheric dispersion
Modelling and simulation of atmospheric dispersion are essential to ensure the safety of emissions emitted into the air by the authorized operation of industrial facilities and to estimate the health consequences of accidents that could affect these facilities. Over the past twenty years, physical dispersion models have undergone significant improvements in order to take into account the details of topography and land use that make real industrial environments complex. Although 3D models have seen their use increase, they have very significant calculation times, which hinders their use in multi-parametric studies and the assessment of uncertainties that require a large number of calculations. It would therefore be desirable to obtain the very precise results of current models or similar results in a much shorter time. Recently, we have developed a strategy consisting of reducing the dimension of distribution maps of an atmospheric pollutant obtained using a reference 3D physical model for different meteorological conditions, then having these maps learned by an artificial intelligence (AI) model which is then used to predict maps in other meteorological situations. The postdoctoral project will focus on complementing the research started by evaluating the performance of dimension reduction and model substitution methods already explored and by studying other methods. Applications will concern, in particular, the simulation of concentrations around an industrial production site that emits gaseous emissions into the atmosphere. The developments will aim to obtain an operational meta-modelling tool.
Preparation and characterization of an oxide/oxide composite
Fiber-reinforced ceramic matrix composites (CMCs) are a class of materials that combine good specific mechanical properties (properties relative to their density) with resistance to high temperatures (> 1000 °C), even in oxidizing atmospheres. They are typically composed of a carbon or ceramic fiber reinforcement and a ceramic matrix (carbide or oxide.
The proposed study focuses on the development of a low-matrix oxide/oxide CMC with suitable dielectric, thermal, and mechanical properties.
This study will be conducted in collaboration with several laboratories at CEA Le Ripault.
Influence of laser bandwidth and wavelength on laser plasma instabilities
As part of the Taranis project initiated by Thales and supported by BPI France and in collaboration with numerous scientific partners such as CEA/DAM, CELIA and LULI, work on target design and definition of the laser intended to energy production in direct drive will take place. A prerequisite for this work is to understand the laser-plasma interaction mechanisms that will occur when the laser is coupled with the target. These deleterious mechanisms for the success of fusion experiments can be regulated by the use of so-called “broadband” lasers. In addition, the choice of the laser wavelength used for the target design and the laser architecture must be defined. The objective of the postdoctoral position is to study the growth and evolution of these instabilities (Brillouin, Raman) in the presence of “broadband” lasers both from an experimental and simulation point of view, and thus to be able to define the laser conditions making it possible to reduce these parametric instabilities.
Evolution of ISAAC and Xpn codes for an extension of the QRPA method to the complete processing of odd nuclei; towards a database without interpolation for odd nuclei
The treatment of odd-isospin nuclei in microscopic approaches is currently limited to the so-called «blocking» approximation. In the Hartree-Fock Bogolyubov (HFB) approach, the ground state of an odd-mass nucleus is described as a one-particle excitation (qp) on its reference vacuum. Thus, in the QRPA approach, where the basic excitations are states «with 2 quasi-particles», the blocked qp is excluded from the valence space under the Pauli exclusion principle. As a result, the chosen qp is a spectator and is not involved in the QRPA collective states. If the single nucleon should have a significant contribution some levels will not be reproduced. The development in the QRPA codes (ISAAC and Xpn) of a procedure that allows all nucleons to participate in collective states is mandatory for a microscopic description of odd nuclei. Moreover, recent Xpn developments have allowed the description of forbidden ß- first decays improving the estimation of half-life time of fission fragments. This could be extended to address ß+ and electronic captures and could be adapted to large-scale calculations useful for nuclear astrophysics.
detection of multiplets and application to turkey-Syria seismic crisis of february 2023
The correlation technique, or template matching, applied to the detection and analysis of seismic events has demonstrated its performance and usefulness in the processing chain of the CEA/DAM National Data Center. Unfortunately, this method suffers from limitations which limit its effectiveness and its use in the operational environment, linked on the one hand to the computational cost of massive data processing, and on the other hand to the rate of false detections that could generate low-level processing. The use of denoising methods upstream of processing (example: deepDenoiser, by Zhu et al., 2020), could also increase the number of erroneous detections. The first part of the research project consists of providing a methodology aimed at improving the processing time performance of the multiplets detector, in particular by using information indexing techniques developed in collaboration with LIPADE (L-MESSI method , Botao Peng, Panagiota Fatourou, Themis Palpanas. Fast Data Series Indexing for In-Memory Data. International Journal on Very Large Data Bases (VLDBJ) 2021). The second part of the project concerns the development of an auto-encoder type “filtering” tool for false detections built using machine learning. The Syria-Turkey seismic crisis of February 2023, dominated by two earthquakes of magnitude greater than 7.0, will serve as a learning database for this study.