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physics.comp-ph2025
Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion application
Jack B. Coughlin, Archis Joglekar, Jonathan Brodrick +1
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 t…
physics.comp-ph2024
Generative Neural Reparameterization for Differentiable PDE-constrained Optimization
Archis S. Joglekar
Partial-differential-equation (PDE)-constrained optimization is a well-worn technique for acquiring optimal parameters of systems governed by PDEs. However, this approach is limite…