Abelian-Higgs Cosmic String Evolution with CUDA

TL;DR

This paper presents a GPU-accelerated simulation code for Abelian-Higgs cosmic string networks, significantly improving computational efficiency and enabling more accurate astrophysical analyses.

Contribution

It introduces a CUDA-based implementation for simulating Abelian-Higgs cosmic strings, enhancing speed and scalability over traditional CPU methods.

Findings

Code achieves good agreement with literature on network scaling properties

Performance bottlenecks are identified and discussed

Potential improvements for scalability are proposed

Abstract

Topological defects form at cosmological phase transitions by the Kibble mechanism, with cosmic strings and superstrings having the most interesting phenomenology. A rigorous analysis of their astrophysical consequences is limited by the availability of accurate numerical simulations, and therefore by hardware resources and computation time. Improving the speed and efficiency of existing codes is therefore essential. All current cosmic string simulations were performed on Central Processing Units. In previous work we presented a General Purpose Graphics Processing Unit implementation of the evolution of cosmological domain wall networks. Here we continue this paradigm shift and discuss an analogous implementation for local Abelian-Higgs strings networks. We discuss the implementation algorithm (including the discretization used and how to calculate network averaged quantities) and then showcase its performance and current bottlenecks. We validate the code by directly comparing our results for the canonical scaling properties of the networks in the radiation and matter eras with those in the literature, finding very good agreement. We finally highlight possible directions for improving the scalability of the code.