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| Paper: |
O-type Stars’ Stellar Parameter Estimation with ANN |
| Volume: |
541, ADASS XXXIII |
| Page: |
189 |
| Authors: |
L.J. Corral; M. Flores; C. Fierro-Santillán; S.G. Navarro |
| DOI: |
10.26624/QIBL1369 |
| Abstract: |
We present the results of the implementation of a deep learning system
capable of estimating the effective temperature and surface gravity of O-type stars. The
proposed system was trained with a database of CMFGEN stellar atmosphere code that
covers stars with Teff from ∼20,000 K to ∼58,000 K, log g from 2.4 to 4.2 dex, and
mass from 9 to 120 M⊙. One of the advantages proposed in this paper include using
a set of equivalent width measurements over the optical region of the stellar spectra,
which avoids processing the full spectra that allows it to apply the same trained system
over different spectra resolutions. |
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