Statistical inference of collision frequencies from x-ray Thomson scattering spectra

TL;DR

This paper investigates how x-ray Thomson scattering spectra can be used to infer collision frequencies in warm dense matter, providing a new diagnostic approach for plasma properties through advanced modeling and inversion techniques.

Contribution

It introduces a method combining Monte Carlo inversion and density functional theory to extract dynamic collision frequencies from XRTS spectra, enhancing plasma diagnostics.

Findings

XRTS spectra are sensitive to collision frequency modeling details.

Monte Carlo inversion effectively retrieves dynamic structure factors.

Results link XRTS signals to plasma electrical conductivity.

Abstract

Thomson scattering spectra measure the response of plasma particles to incident radiation. In warm dense matter, which is opaque to visible light, x-ray Thomson scattering (XRTS) enables a detailed probe of the electron distribution and has been used as a diagnostic for electron temperature, density, and plasma ionization. In this work, we examine the sensitivities of inelastic XRTS signatures to modeling details including the dynamic collision frequency and the electronic density of states. Applying verified Monte Carlo inversion methods to dynamic structure factors obtained from time-dependent density functional theory, we assess the utility of XRTS signals as a way to inform the dynamic collision frequency, especially its direct-current (DC) limit, which is directly related to the electrical conductivity.