J/A+A/687/A205 Stellar parameters of 286 CARMENES M dwarfs (Mas-Buitrago+, 2024)
Using autoencoders and deep transfer learning to determine the stellar
parameters of 286 CARMENES M dwarfs.
Mas-Buitrago P., Gonzalez-Marcos A., Solano E., Passegger V.M.,
Cortes-Contreras M., Ordieres-Mere J., Bello-Garcia A., Caballero J.A.,
Schweitzer A., Tabernero H.M., Montes D., Cifuentes C.
<Astron. Astrophys. 687, A205 (2024)>
=2024A&A...687A.205M 2024A&A...687A.205M (SIMBAD/NED BibCode)
ADC_Keywords: Stars, M-type ; Stars, dwarfs ; Spectroscopy
Keywords: methods: data analysis - techniques: spectroscopic -
stars: fundamental parameters - stars: late-type - stars: low-mass
Abstract:
Deep learning (DL) techniques are a promising approach among the set
of methods used in the ever-challenging determination of stellar
parameters in M dwarfs. In this context, transfer learning could play
an important role in mitigating uncertainties in the results due to
the synthetic gap (i.e. difference in feature distributions between
observed and synthetic data).
We propose a feature-based deep transfer learning (DTL) approach based
on autoencoders to determine stellar parameters from high-resolution
spectra. Using this methodology, we provide new estimations for the
effective temperature, surface gravity, metallicity, and projected
rotational velocity for 286 M dwarfs observed by the CARMENES survey.
Using autoencoder architectures, we projected synthetic PHOENIX-ACES
spectra and observed CARMENES spectra onto a new feature space of
lower dimensionality in which the differences between the two domains
are reduced. We used this low-dimensional new feature space as input
for a convolutional neural network to obtain the stellar parameter
determinations.
We performed an extensive analysis of our estimated stellar
parameters, ranging from 3050 to 4300K, 4.7 to 5.1dex, and -0.53 to
0.25dex for Teff, logg, and [Fe/H], respectively. Our results are
broadly consistent with those of recent studies using CARMENES data,
with a systematic deviation in our Teff scale towards hotter values
for estimations above 3750K. Furthermore, our methodology mitigates
the deviations in metallicity found in previous DL techniques due to
the synthetic gap.
We consolidated a DTL-based methodology to determine stellar
parameters in M dwarfs from synthetic spectra, with no need for
high-quality measurements involved in the knowledge transfer. These
results suggest the great potential of DTL to mitigate the differences
in feature distributions between the observations and the PHOENIX-ACES
spectra.
Description:
Stellar atmospheric parameters of 286 CARMENES M dwarfs determined
using our deep transfer learning methodology.
File Summary:
--------------------------------------------------------------------------------
FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
tablea1.dat 128 286 The catalogue
--------------------------------------------------------------------------------
Byte-by-byte Description of file: tablea1.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 11 A11 --- Karmn CARMENES identifier (JHHMMm+DDdA)
13- 35 A23 --- Name Discovery or most common name (1)
37- 52 F16.11 deg RAdeg ? Right ascension (J2000.0) (2)
54- 68 F15.11 deg DEdeg ? Declination (J2000.0) (2)
70- 73 I4 K Teff Effective temperature from our methodology
75- 77 I3 K e_Teff Delta Teff for -1 sigma
79- 81 I3 K E_Teff Delta Teff for +1 sigma
83- 86 F4.2 [cm/s2] logg Surface gravity from our methodology
88- 91 F4.2 [cm/s2] e_logg Delta logg for -1 sigma
93- 96 F4.2 [cm/s2] E_logg Delta logg for +1 sigma
98-102 F5.2 [Sun] [M/H] Metallicity from our methodology
104-107 F4.2 [Sun] e_[M/H] Delta [M/H] for -1 sigma
109-112 F4.2 [Sun] E_[M/H] Delta [M/H] for +1 sigma
114-118 F5.2 [km/s] vsini Projected rotational velocity from our
methodology
120-123 F4.2 [km/s] e_vsini Delta vsini for -1 sigma
125-128 F4.2 [km/s] E_vsini Delta vsini for +1 sigma
--------------------------------------------------------------------------------
Note (1): From Cifuentes et al. (2020A&A...642A.115C 2020A&A...642A.115C, Cat. J/A+A/642/A115)
Note (2): Equatorial coordinates at epoch J2016.0 in equinox J2000,
from Gaia DR3.
--------------------------------------------------------------------------------
Acknowledgements:
Pedro Mas-Buitrago, pmas(at)cab.inta-csic.es
(End) Patricia Vannier [CDS] 13-May-2024