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Computing Mixed Opacities with a Physics-Constrained Machine Learning Surrogate

https://doi.org/10.2139/ssrn.6996785
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/0098-3004(93)90090-ropenalex-snapshot
Principal components analysis (PCA)
inferredcites →https://doi.org/10.1046/j.1365-8711.1998.01687.xopenalex-snapshot
Accurate free—free Gaunt factors for astrophysical plasmas
inferredcites →https://doi.org/10.1063/5.0006784openalex-snapshot
Deep learning for NLTE spectral opacities
inferredcites →https://doi.org/10.1080/14786442308565244openalex-snapshot
XCIII. On the theory of X-ray absorption and of the continuous X-ray spectrum
inferredcites →https://doi.org/10.1088/0067-0049/209/2/36openalex-snapshot
RADIATION TRANSPORT FOR EXPLOSIVE OUTFLOWS: A MULTIGROUP HYBRID MONTE CARLO METHOD
inferredcites →https://doi.org/10.1088/0067-0049/214/2/28openalex-snapshot
RADIATION TRANSPORT FOR EXPLOSIVE OUTFLOWS: OPACITY REGROUPING
inferredcites →https://doi.org/10.1093/mnras/staa485openalex-snapshot
A line-binned treatment of opacities for the spectra and light curves from neutron star mergers
inferredcites →https://doi.org/10.1093/mnras/sty1018openalex-snapshot
Impact of ejecta morphology and composition on the electromagnetic signatures of neutron star mergers
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