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google-deepmind/torax

TORAX: Tokamak transport simulation in JAX

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created
5 Mar 2024
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5h ago
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README

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[](https://github.com/google-deepmind/torax/actions/workflows/pytest.yml) ## What is TORAX? TORAX is a differentiable tokamak core transport simulator aimed for fast and accurate forward modelling, pulse-design, trajectory optimization, and controller design workflows. TORAX is written in Python using JAX, with the following motivations: - Open-source and extensible, aiding with flexible workflow coupling - JAX provides auto-differentiation capabilities and code compilation for fast runtimes. Differentiability allows for gradient-based nonlinear PDE solvers for fast and accurate modelling, and for sensitivity analysis of simulation results to arbitrary parameter inputs, enabling applications such as trajectory optimization and data-driven parameter identification for semi-empirical models. Auto-differentiability allows for these applications to be easily extended with the addition of new physics models, including ML-surrogates, or new parameter inputs, by avoiding the need to hand-derive Jacobians

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