The ASAS-SN catalogue of variable stars – IV. Periodic variables in the APOGEE survey

Abstract

We explore the synergy between photometric and spectroscopic surveys by searching for periodic variable stars among the targets observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) using photometry from the All-Sky Automated Survey for Supernovae (ASAS-SN). We identified 1924 periodic variables among more than $258\, 000$ APOGEE targets; 465 are new discoveries. We homogeneously classified 430 eclipsing and ellipsoidal binaries, 139 classical pulsators (Cepheids, RR Lyrae, and δ Scuti), 719 long-period variables (pulsating red giants), and 636 rotational variables. The search was performed using both visual inspection and machine learning techniques. The light curves were also modelled with the damped random walk stochastic process. We find that the median [Fe/H] of variable objects is lower by 0.3 dex than that of the overall APOGEE sample. Eclipsing binaries and ellipsoidal variables are shifted to a lower median [Fe/H] by 0.2 dex. Eclipsing binaries and rotational variables exhibit significantly broader spectral lines than the rest of the sample. We make ASAS-SN light curves for all the APOGEE stars publicly available and provide parameters for the variable objects.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 21, 2019
Source ID
10.1093/mnras/stz1681

Entities

People

  • B J Shappee
  • C A Britt
  • C. S. Kochanek
  • D Will
  • G Pojmanski
  • J L Prieto
  • J V Shields
  • K Z Stanek
  • Michał Pawlak
  • Ondřej Pejcha
  • P Jakubčík
  • Sheng Dong
  • T Jayasinghe
  • Thomas W.-S. Holoien
  • Todd A. Thompson

Organizations

  • Alfred P. Sloan Foundation
  • California Institute of Technology
  • Carnegie Institution for Science
  • Charles University
  • Chinese Academy of Sciences
  • Diego Portales University
  • European Research Council
  • European Space Agency
  • Framework Programmes for Research and Technological Development
  • Gordon and Betty Moore Foundation
  • Institute for Advanced Study
  • Johns Hopkins University
  • Los Alamos National Laboratory
  • Max Planck Society
  • Millennium Institute of Astrophysics
  • Ministry of Education
  • National Aeronautics and Space Administration
  • National Fund for Scientific and Technological Development
  • National Natural Science Foundation of China
  • National Sleep Foundation
  • New Mexico State University
  • Ohio State University
  • Peking University
  • Princeton University
  • Simons Foundation
  • United States Department of Energy
  • United States Naval Observatory
  • University of Chicago
  • University of Hawaiʻi System
  • University of Massachusetts
  • University of Oxford
  • University of Pittsburgh
  • University of Warsaw
  • University of Washington

Tags

Fields of Study

  • Physics

Readers

  • Astronomy/Astrophysics
  • Space/Atmospheric Physics.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms