Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion application
Abstract
This work presents a case study of a heterogeneous multiphysics solver from the nuclear fusion domain. At the macroscopic scale, an auto-differentiable ODE solver in JAX computes the evolution of the pulsed power circuit and bulk plasma parameters for a compressing Z Pinch. The ODE solver requires a closure for the impedance of the plasma load obtained via root-finding at every timestep, which we solve efficiently using gradient-based Newton iteration. However, incorporating non-differentiable production-grade plasma solvers like Gkeyll (a C/CUDA plasma simulation suite) into a gradient-based workflow is non-trivial. The ''Tesseract'' software addresses this challenge by providing a multi-physics differentiable abstraction layer made fully compatible with JAX (through the `tesseract_jax` adapter). This architecture ensures end-to-end differentiability while allowing seamless interchange between high-fidelity solvers (Gkeyll), neural surrogates, and analytical approximations for rapid, progressive prototyping.
Cite
@article{arxiv.2511.13262,
title = {Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion application},
author = {Jack B. Coughlin and Archis Joglekar and Jonathan Brodrick and Alexander Lavin},
journal= {arXiv preprint arXiv:2511.13262},
year = {2025}
}