| Title |
A method to derive self-consistent NLTE astrophysical parameters for four million high-resolution 4MOST stellar spectra in half a day with invertible neural networks |
| Authors |
Ksoll, Victor F ; Storm, Nicholas ; Bergemann, Maria ; Lee, Katherine ; Klessen, Ralf S ; Albarracín, R ; Guiglion, Guillaume ; Tautvaišienė, Gražina |
| DOI |
10.1051/0004-6361/202558595 |
| Full Text |
|
| Is Part of |
Astronomy & Astrophysics.. Les Ulis : EDP Sciences. 2026, vol. 708, art. no. A118, p. [1-25].. ISSN 0004-6361. eISSN 1432-0746 |
| Keywords [eng] |
methods: statistical ; techniques: spectroscopic ; stars: abundances ; stars: atmospheres |
| Abstract [eng] |
Context . Modern spectroscopic surveys have the capacity to obtain the spectra of millions of stars. However, classical spectroscopic methods can often be computationally expensive, rendering them impractical for the analysis of large datasets. |
| Published |
Les Ulis : EDP Sciences |
| Type |
Journal article |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
