A large and pristine sample of standard candles across the Milky Way: ~100,000 red clump stars with 3% contamination

TL;DR

This study develops a data-driven method to identify a large, high-purity sample of red clump stars across the Milky Way using low-resolution spectroscopic data, enabling improved galactic structure mapping.

Contribution

It introduces a novel spectral mapping technique that reduces contamination in red clump star identification to about 3%, even with low-resolution spectra.

Findings

Identified over 210,000 RC stars with ~9% contamination.

Provided a high-purity RC sample of 92,249 stars with ~3% contamination.

Demonstrated the effectiveness of low-resolution spectra for large-scale galactic studies.

Abstract

Core helium-burning red clump (RC) stars are excellent standard candles in the Milky Way. These stars may have more precise distance estimates from spectrophotometry than from Gaia parallaxes beyond 3 kpc. However, RC stars have $T_{\rm eff}$ and log g very similar to some red giant branch (RGB) stars. Especially for low-resolution spectroscopic studies where $T_{\rm eff}$, log g, and [Fe/H] can only be estimated with limited precision, separating RC stars from RGB through established method can incur ~20% contamination. Recently, Hawkins et al. (2018) demonstrated that the additional information in single-epoch spectra, such as the C/N ratio, can be exploited to cleanly differentiate RC and RGB stars. In this second paper of the series, we establish a data-driven mapping from spectral flux space to independently determined asteroseismic parameters, the frequency and the period spacing. From this, we identify 210,371 RC stars from the publicly available LAMOST DR3 and APOGEE DR14 data, with ~9% of contamination. We provide an RC sample of 92,249 stars with a contamination of only ~3%, by restricting the combined analysis to LAMOST stars with ${\rm S/N}_{\rm pix}$ > 75. This demonstrates that high-S/N, low-resolution spectra covering a broad wavelength range can identify RC samples at least as pristine as their high-resolution counterparts. As coming and ongoing surveys such as TESS, DESI, and LAMOST will continue to improve the overlapping training spectroscopic-asteroseismic sample, the method presented in this study provides an efficient and straightforward way to derive a vast yet pristine RC stars to reveal the 3D structure of the Milky Way.