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Harnessing machine learning for accurate treatment of overlapping opacity species in GCMs. (arXiv:2311.00775v1 [astro-ph.EP])
cs.LG updates on arXiv.org arxiv.org
To understand high precision observations of exoplanets and brown dwarfs, we
need detailed and complex general circulation models (GCMs) that incorporate
hydrodynamics, chemistry, and radiation. In this study, we specifically examine
the coupling between chemistry and radiation in GCMs and compare different
methods for mixing opacities of different chemical species in the correlated-k
assumption, when equilibrium chemistry cannot be assumed. We propose a fast
machine learning method based on DeepSets (DS), which effectively combines
individual correlated-k opacities (k-tables). We evaluate …
arxiv astro chemistry exoplanets general machine machine learning precision study treatment