J/MNRAS/524/1855 Revised stars atmos. param. from GaiaXP DR3 sp (Zhang+, 2023)
Parameters of 220 million stars from Gaia BP/RP spectra.
Zhang X., Green G.M., Rix H.-W.
<Mon. Not. R. Astron. Soc. 524, 1855-1884 (2023)>
=2023MNRAS.524.1855Z 2023MNRAS.524.1855Z (SIMBAD/NED BibCode)
ADC_Keywords: Stars, atmospheres ; Effective temperatures ; Abundances, [Fe/H] ;
Reddening ; Photometry, infrared ; Optical ; Spectroscopy ;
Extinction ; Positional data ; Parallaxes, trigonometric
Keywords: techniques: spectroscopic; catalogues; stars: fundamental parameters
Galaxy: stellar content; dust, extinction
Abstract:
We develop, validate and apply a forward model to estimate stellar
atmospheric parameters (Teff, log g, and [Fe/H]), revised distances
and extinctions for 220 million stars with XP spectra from Gaia DR3.
Instead of using ab initio stellar models, we develop a data-driven
model of Gaia XP spectra as a function of the stellar parameters, with
a few straightforward built-in physical assumptions. We train our
model on stellar atmospheric parameters from the LAMOST survey, which
provides broad coverage of different spectral types. We model the Gaia
XP spectra with all of their covariances, augmented by 2MASS and WISE
photometry that greatly reduces degeneracies between stellar
parameters, yielding more precise determinations of temperature and
dust reddening. Taken together, our approach overcomes a number of
important limitations that the astrophysical parameters released in
Gaia DR3 faced, and exploits the full information content of the data.
We provide the resulting catalogue of stellar atmospheric parameters,
revised parallaxes, and extinction estimates, with all their
uncertainties. The modelling procedure also produces an estimate of
the optical extinction curve at the spectral resolution of the XP
spectra (R ∼ 20-100), which agrees reasonably well with the
R(V) = 3.1 CCM model. Remaining limitations that will be addressed in
future work are that the model assumes a universal extinction law,
ignores binary stars and does not cover all parts of the
Hertzsprung-Russell Diagram (e.g. white dwarfs).
Description:
We infer stellar parameters using three sources of spectrophotometric
data (Gaia XP in the optical, 2MASS in the near infrared, and unWISE
in the infrared), as well as Gaia parallaxes. We additionally make use
of stellar atmospheric parameter estimates based on LAMOST optical
spectroscopy. As of Gaia DR3 (I/355), BP/RP spectra (hereafter "XP
spectra") of ∼220 million stars have been published. We use the AFGK
catalogue from LAMOST Data Release 8 (DR11, V/162), which contains
atmospheric parameters of over 6 million stars. For hot stars
(Teff≥7500K), we obtain stellar atmospheric parameters from the
"Hot Payne" (Xiang et al. 2022A&A...662A..66X 2022A&A...662A..66X, J/A+A/662/A66), which
applies the method, "The Payne" (Ting et al. 2019ApJ...879...69T 2019ApJ...879...69T,
J/ApJ/879/69) to determine the atmospheric parameters of O-, B-, and
A-type stars in LAMOST Data Release 6. We cross-match LAMOST with Gaia
DR3 by searching the closest star, out to a maximum angular separation
of 0.25". We use the cross-matched 2MASS data from the Gaia Archive.
We make use of the unWISE "neo6" catalogue, which is based on WISE
exposures captured through 2019 December 13.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
xpparams.sam 173 1000 Astrometrics and revised stellar atmospheric
parameters of Gaia XP stars inferred from our
data-driven model with straightforward built-in
physical assumptions
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See also:
J/MNRAS/505/5978 : Gaia EDR3 view on Galactic globular clusters
(Vasiliev+, 2021)
J/ApJ/879/69 : The Payne applied to the APOGEE DR14 data set (Ting+, 2019)
J/ApJ/792/30 : NEOWISE magnitudes for near-Earth objects (Mainzer+, 2014)
J/ApJ/743/156 : NEOWISE observations of NEOs: preliminary results
(Mainzer+, 2011)
J/A+A/673/A155 : StarHorse data for 8 spectroscopic surveys (Queiroz+, 2023)
J/ApJ/663/320 : IR-through-UV extinction curve (Fitzpatrick+, 2007)
J/A+A/662/A66 : Hot stars from LAMOST DR6 (Xiang+, 2022)
VII/233 : 2MASS All-Sky Extended Source Catalog (XSC)
(IPAC-UMass, 2003-2006)
II/363 : The band-merged unWISE Catalog (Schlafly+, 2019)
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
I/337 : Gaia DR1 (Gaia Collaboration, 2016)
Byte-by-byte Description of file: xpparams.sam
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Bytes Format Units Label Explanations
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1- 19 I19 --- GaiaDR3 Gaia DR3 unique source identifier
(gdr3sourceid)
21- 30 F10.6 deg RA_ICRS Truncated Gaia DR3 ICRS right ascension for
this object (ICRS) at Ep=2016.0 (ra)
32- 41 F10.6 deg DE_ICRS Truncated Gaia DR3 ICRS declination for
this object (ICRS) at Ep=2016.0 (dec)
43- 49 F7.4 10+3K Teff Estimated effective Temperature (teff)
51- 58 F8.4 10+3K e_Teff Error in estimated effective temperature
(err_teff)
60- 66 F7.4 [Sun] [Fe/H] Log of estimated Fe/H iron to hydrogen
ratio (fe_h)
68- 75 F8.4 [Sun] e_[Fe/H] Error in [Fe/H] (errfeh)
77- 83 F7.4 [Sun] logg Log of estimated surface gravity (logg)
85- 92 F8.4 [Sun] e_logg Error of logg (err_logg)
94- 101 F8.4 mag Ext Estimated extinction parameter (ext) (1)
103- 110 F8.4 mag e_Ext Error of Ext (err_ext)
112- 119 F8.4 mas Plx Parallax estimated from the model
(mod_parallax)
121- 128 F8.4 mas e_Plx Error in the parallax estimated from the
model (errmodparallax)
130- 131 I2 --- Quality Quality flags in which the three least
significant bits represent whether the
confidence in effective temperature, [Fe/H]
and log(g) is less than 0.5, respectively
(quality_flags) (2)
133- 142 A10 --- Chi2 The Χ2 of the best-fit solution,
divide by 61 to obtain Χ2 per degree
of freedom (chi2_opt)
144- 152 F9.4 [-] ln(Prior) Natural log of the GMM prior on stellar
type, at the location of the optimal
solution (ln_prior)
154- 159 F6.4 --- ConfTeff A neural-network-based estimate of the
confidence in the effective temperature
estimate, on a scale of 0 as no confidence
to 1 as high confidence (teff_confidence)
161- 166 F6.4 --- Conf[Fe/H] A neural-network-based estimate of the
confidence in the [Fe/H] estimate, on a
scale of 0 as no confidence to 1 as high
confidence (feh_confidence)
168- 173 F6.4 --- Conflogg A neural-network-based estimate of the
confidence in the log(g) estimate, on a
scale of 0 as no confidence as to 1 as high
confidence (logg_confidence)
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Note (1): To convert to the extension at a particular wavelength, multiply
this by that wavelength's value in the extinction curve, available
at
(https://zenodo.org/record/7811871/files/
extinction_curve.txt?download=1) and in the footnote.
Note (2): The 4th bit is set if chi2_opt/61 > 2. The 5th bit is set if
ln_prior < -7.43. The 6th bit is set if our parallax estimate is
more than 10 sigma from the GDR3 measurement (using reported parallax
uncertainties from GDR3). The two most significant bits are always
unset. We recommend a cut of quality_flags < 8 (the "basic
reliability cut"), although a stricter cut of quality_flags ≡ 0
ensures higher reliability at the cost of lower completeness.
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History:
From electronic version of the journal
License: CC-BY-4.0
(End) Luc Trabelsi [CDS] 11-Sep-2026