Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion application

• URL: http://arxiv.org/abs/2511.13262v1
• Date: Mon, 17 Nov 2025 11:23:16 GMT
• Title: Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion application
• Authors: Jack B. Coughlin, Archis Joglekar, Jonathan Brodrick, Alexander Lavin,
• Abstract summary: This work presents a case study of a heterogeneous multiphysics solver from the nuclear fusion domain.<n>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.<n>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.
• Score: 39.74211852563065
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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