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.