Mosaic: A Benchmark Suite for Differentiable Physics Solvers
Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse problems, yet the practical cost of obtaining correct, usable gradients from a given solver on a given problem is largely undocumented. Integration effort, computational cost, gradient accuracy, and numerical conditioning vary widely across solvers and are discoverable only by trial and error. We introduce Mosaic, an extensible benchmarking framework for differentiable PDE solvers that standardizes access to solver gradients. Each solver is packaged as a containerized component (Tesseract) exposing a uniform gradient API regardless of language or ...
| Authors | Andrin Rehmann, Heiko Zimmermann, Dion Häfner |
|---|---|
| Primary category | physics.comp-ph |
| Published | 26 June 2026 |
| Last updated at source | 26 June 2026 |
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