soliton_solver: A GPU-based finite-difference PDE solver for topological solitons in two-dimensional non-linear field theories

TL;DR

soliton_solver is an open-source GPU-accelerated software for simulating and visualizing topological solitons in various two-dimensional non-linear field theories, enabling broad scientific applications with real-time capabilities.

Contribution

It introduces a modular, theory-agnostic GPU-based framework for simulating topological solitons across diverse physical systems in a single computational environment.

Findings

Supports real-time visualization of soliton dynamics.

Flexible architecture for incorporating new physical theories.

Efficient GPU-based numerical computations for large-scale simulations.

Abstract

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.