An end-to-end differentiable JAX pipeline couples 1D hydrodynamics, time-dependent chemistry, and radiative transfer, and recovers shock and rate parameters from synthetic HCO+ spectra.
Fast GPU-Powered and Auto-Differentiable Forward Modeling of IFU Data Cubes
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abstract
We present RUBIX, a fully tested, well-documented, and modular Open Source tool developed in JAX, designed to forward model IFU cubes of galaxies from cosmological hydrodynamical simulations. The code automatically parallelizes computations across multiple GPUs, demonstrating performance improvements over state-of-the-art codes by a factor of 600. This optimization reduces compute times from hours to only seconds. RUBIX leverages JAX's auto-differentiation capabilities to enable not only forward modeling but also gradient computations through the entire pipeline paving the way for new methodological approaches such as e.g. gradient-based optimization of astrophysics model parameters. RUBIX is open-source and available on GitHub: https://github.com/ufuk-cakir/rubix.
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astro-ph.IM 1years
2026 1verdicts
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End-to-end differentiable retrieval of molecular spectra using hydrodynamics, chemistry, and radiative transfer
An end-to-end differentiable JAX pipeline couples 1D hydrodynamics, time-dependent chemistry, and radiative transfer, and recovers shock and rate parameters from synthetic HCO+ spectra.