KineticXGPU: A Tensorized Collision Operator for Dark-Sector Self-Scattering

Abstract

We present KineticXGPU, a PyTorch-based implementation of the \(2\to2\) elastic self-collision operator for dark-sector momentum distributions. The discretized collision operator can be expressed as tensor contractions and is therefore well suited for GPUs. As an application, we study a two-source freeze-in scenario in which the final distribution can develop a bimodal shape. We show that increasing the strength of elastic self-interactions progressively erases this structure and drives the distribution toward a Maxwell--Boltzmann distribution. We find that $2\to 2$ self-interactions can reduce the warmness of nonthermal frozen-in dark matter, illustrating how they may alleviate structure-formation constraints in late-decay scenarios. We compare the phase-space formulation with a set of fluid equations that couple the number density and velocity dispersion. We also compare CPU and GPU runtimes and demonstrate the computational advantage of the tensorized approach. The code is publicly available on GitHub.

arXiv comment29 pages, 13 figures