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ABSTRACT Large pristine samples of red clump stars are highly sought after given that they are standard candles and give precise distances even at large distances. However, it is difficult to cleanly select red clumps stars because they can have the same Teff and log g as red giant branch stars. Recently, it was shown that the asteroseismic parameters, $$\rm {\Delta }$$P and $$\rm {\Delta \nu }$$, which are used to accurately select red clump stars, can be derived from spectra using the change in the surface carbon to nitrogen ratio ([C/N]) caused by mixing during the red giant branch. This change in [C/N] can also impact the spectral energy distribution. In this study, we predict the $$\rm {\Delta }$$P, $$\rm {\Delta \nu }$$, Teff, and log g using 2MASS, AllWISE, Gaia, and Pan-STARRS data in order to select a clean sample of red clump stars. We achieve a contamination rate of ∼20 per cent, equivalent to what is achieved when selecting from Teff and log g derived from low-resolution spectra. Finally, we present two red clump samples. One sample has a contamination rate of ∼20 per cent and ∼405 000 red clump stars. The other has a contamination of ∼33 per cent and ∼2.6 million red clump stars that includes ∼75 000 stars at distances >10 kpc. For |b| > 30 deg, we find ∼15 000 stars with contamination rate of ∼9 per cent. The scientific potential of this catalogue for studying the structure and formation history of the Galaxy is vast, given that it includes millions of precise distances to stars in the inner bulge and distant halo where astrometric distances are imprecise.
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Spectroscopic Distance, Mass, and Age Estimations for APOGEE DR17
Abstract We derive distances and masses of stars from the Sloan Digital Sky Survey (SDSS) Apache Point Observatory Galactic Evolution Experiment Data Release 17 using simple neural networks. Training data for distances comes from Gaia EDR3, supplemented by literature distances for star clusters. For masses, the network is trained using asteroseismic masses for evolved stars and isochrone masses for main-sequence stars. The models are trained on effective temperature, surface gravity, metallicity, and carbon and nitrogen abundances. We found that our distance predictions have median fractional errors that range from ≈20% at low loggand ≈10% at higher loggwith a standard deviation of ≈11%. The mass predictions have a standard deviation of ±12%. Using the masses, we derive ages for evolved stars based on the correspondence between mass and age for giant stars given by isochrones. The results are compiled into a Value Added Catalog called DistMass that contains distances and masses for 733,901 independent spectra, plus ages for 396,548 evolved stars.
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- Award ID(s):
- 1909897
- PAR ID:
- 10487398
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astronomical Journal
- Volume:
- 167
- Issue:
- 2
- ISSN:
- 0004-6256
- Format(s):
- Medium: X Size: Article No. 73
- Size(s):
- Article No. 73
- Sponsoring Org:
- National Science Foundation
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