Monte-Carlo Event Generation for X-Ray Thomson Scattering Analysis

TL;DR

This paper introduces an event-driven Monte Carlo method for X-ray Thomson scattering analysis in warm-dense matter, improving efficiency and flexibility by sampling individual scattering events.

Contribution

It adapts particle physics event-generation techniques to XRTS modeling, enabling scalable, model-agnostic analysis with reduced computational costs.

Findings

Feasibility demonstrated for non-resonant XRTS in synthetic setups.

Method preserves full kinematic information and allows flexible detector simulations.

Decouples event generation from detector analysis for efficiency.

Abstract

A key diagnostic in warm-dense matter (WDM) experiments is X-ray Thomson scattering (XRTS), but its interpretation is often limited by complex instrument effects and the high computationally expensive combinations of microscopic models with detector simulations. We present a proof-of-principle implementation of an event-driven approach to XRTS modelling, inspired by particle physics event-generators. Instead of computing the spectra via forward models, individual scattering events are sampled from the differential cross section and sent through a spectrometer simulation. This provides a statistically consistent representation that preserves full kinematic information and enables flexible and geometry-aware analysis. We demonstrate the feasibility and physical consistency of the method for non-resonant XRTS in a synthetic setup. By decoupling event generation from detector-level analysis, the framework allows efficient reuse of the sampled events and reduces computational overhead associated with repeated evaluations. The method is model-agnostic and establishes a new connection between particle-physics event generation techniques and WDM diagnostics, providing a scalable foundation for advanced XRTS analysis and inference.