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Bibliographic Details
Main Author: Leask, Paul
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.24370
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author Leask, Paul
author_facet Leask, Paul
contents This paper introduces soliton_solver, an open-source GPU-accelerated software package for the simulation and real-time visualization of topological solitons in two-dimensional non-linear field theories. The software is structured around a theory-agnostic numerical core implemented using Numba CUDA kernels, while individual physical models are introduced through modular theory components. This separation enables a single computational framework to be applied across a broad class of systems, from nanoscale magnetic spin textures in condensed matter physics to cosmic strings spanning galaxies in high energy physics. The numerical backend provides finite-difference discretization, energy minimization, and GPU-resident evaluation of observables. A CUDA--PyOpenGL rendering pipeline allows direct visualization of evolving field configurations without staging full arrays through host memory. The package is distributed in Python via PyPI and supports both reproducible batch simulations and interactive exploration of metastable configurations, soliton interactions, and model-dependent initial states. We describe the software architecture, numerical workflow, and extensibility model, and we present representative example applications. We also outline how additional theories can be incorporated with minimal modification of the shared numerical infrastructure.
format Preprint
id arxiv_https___arxiv_org_abs_2603_24370
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle soliton_solver: A GPU-based finite-difference PDE solver for topological solitons in two-dimensional non-linear field theories
Leask, Paul
High Energy Physics - Theory
Mesoscale and Nanoscale Physics
Superconductivity
Computational Physics
This paper introduces soliton_solver, an open-source GPU-accelerated software package for the simulation and real-time visualization of topological solitons in two-dimensional non-linear field theories. The software is structured around a theory-agnostic numerical core implemented using Numba CUDA kernels, while individual physical models are introduced through modular theory components. This separation enables a single computational framework to be applied across a broad class of systems, from nanoscale magnetic spin textures in condensed matter physics to cosmic strings spanning galaxies in high energy physics. The numerical backend provides finite-difference discretization, energy minimization, and GPU-resident evaluation of observables. A CUDA--PyOpenGL rendering pipeline allows direct visualization of evolving field configurations without staging full arrays through host memory. The package is distributed in Python via PyPI and supports both reproducible batch simulations and interactive exploration of metastable configurations, soliton interactions, and model-dependent initial states. We describe the software architecture, numerical workflow, and extensibility model, and we present representative example applications. We also outline how additional theories can be incorporated with minimal modification of the shared numerical infrastructure.
title soliton_solver: A GPU-based finite-difference PDE solver for topological solitons in two-dimensional non-linear field theories
topic High Energy Physics - Theory
Mesoscale and Nanoscale Physics
Superconductivity
Computational Physics
url https://arxiv.org/abs/2603.24370