Graph neural networks can approximate full 3D non-LTE Ca II populations in solar models with correlations above 0.99 and extreme computational efficiency.
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A new numerical method for full non-LTE multi-level radiative transfer with broadened levels shows that standard NLTE with partial redistribution is sufficient for Ca II spectral lines in the studied simplified case.
3D RT in a MURaM-ChE enhanced network simulation produces Mg II h&k lines closer to IRIS data than 1.5D, showing larger 1.5D-3D discrepancies than Bifrost due to horizontal velocities and more scatter in correlations.
CS peak fractional abundances of 1-4e-6 and e-folding radii of 1.8-6.8e16 cm are derived for five carbon-rich AGB stars, showing no major differences from IRC+10216 beyond density effects and matching chemical model predictions.
citing papers explorer
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Accelerating 3D Non-LTE Synthesis with Graph Neural Networks
Graph neural networks can approximate full 3D non-LTE Ca II populations in solar models with correlations above 0.99 and extreme computational efficiency.
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Full non-LTE multi-level radiative transfer II. The case of a 5-level Ca ii atom with broadened excited levels
A new numerical method for full non-LTE multi-level radiative transfer with broadened levels shows that standard NLTE with partial redistribution is sufficient for Ca II spectral lines in the studied simplified case.
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Mg II h&k spectral line properties computed using 3D radiative transfer in an enhanced network region simulated with the MURaM-ChE code
3D RT in a MURaM-ChE enhanced network simulation produces Mg II h&k lines closer to IRIS data than 1.5D, showing larger 1.5D-3D discrepancies than Bifrost due to horizontal velocities and more scatter in correlations.
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Charting circumstellar chemistry of carbon-rich asymptotic giant branch stars. II. Abundances and spatial distributions of CS
CS peak fractional abundances of 1-4e-6 and e-folding radii of 1.8-6.8e16 cm are derived for five carbon-rich AGB stars, showing no major differences from IRC+10216 beyond density effects and matching chemical model predictions.