Two-component Bayesian modeling in the data analysis of collective Thomson scattering

Abstract

We apply Bayesian inference to the analysis of collective Thomson scattering (CTS) spectra, a diagnostic technique for determining local plasma parameters. Using the population annealing Monte Carlo (PAMC) method, we evaluate the posterior probability density functions (PDFs) for six plasma parameters. The analysis is performed separately for the ion acoustic wave (IAW) and electron plasma wave (EPW) features and jointly for both features. The results show that the combined analysis provides constraints on all six parameters, although the degree of constraint depends on the parameter, whereas the separate analyses provide strong constraints only on complementary subsets of the parameters. In particular, the combined analysis provides a clear constraint on the ion charge state, which is not determined by either separate analysis alone. These findings demonstrate the importance of Bayesian modeling that accounts for the two-component nature of plasmas, consisting of ions and electrons.

arXiv comment11 pages, 9 figures. Accepted for publication in Plasma and Fusion Research on October 16, 2026