From the inner to outer Milky Way: a photometric sample of 2.6 million red clump stars

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, ΔP and Δν⁠, 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 ΔP, Δν⁠, 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 impreciseThis project was initiated in the Kavli Summer Program in Astrophysics held at University of California, Santa Cruz in 2019, funded by the Kavli Foundation and by the National Science Foundation. We thank them for their generous support. Madeline Lucey acknowledges support from the Wootton Center for Astrophysical Plasma Properties under the United States Department of Energy collaborative agreement DE-NA0003843. Yuan-Sen Ting is grateful to be supported by the National Aeronautics and Space Administration (NASA) Hubble Fellowship grant HST-HF2-51425.001 awarded by the Space Telescope Science Institute. Nesar Ramachandra is partially supported under the U.S. Department of Energy contract DE-AC02-06CH11357 for the work at Argonne National Laboratory. Keith Hawkins has been partially supported by a TDA/Scialog grant funded by the Research Corporation and a Scialog grant funded by the Heising-Simons Foundation. Keith Hawkins acknowledges support from the National Science Foundation grant AST-1907417. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing high performance computing resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, ht tps://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundatio