CaltechAUTHORS
  A Caltech Library Service

Long-period High-amplitude Red Variables in the KELT Survey

Arnold, R. Alex and McSwain, M. Virginia and Pepper, Joshua and Whitelock, Patricia A. and Hernitschek, Nina and James, David J. and Kuhn, Rudolf B. and Lund, Michael B. and Rodriguez, Joseph E. and Siverd, Robert J. and Stassun, Keivan G. (2020) Long-period High-amplitude Red Variables in the KELT Survey. Astrophysical Journal Supplement Series, 247 (2). Art. No. 44. ISSN 1538-4365. https://resolver.caltech.edu/CaltechAUTHORS:20200316-150528185

[img] PDF - Published Version
See Usage Policy.

3716Kb
[img] PDF - Accepted Version
See Usage Policy.

1601Kb

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20200316-150528185

Abstract

We present a sample of 4132 Mira-like variables (red variables with long periods and high amplitudes) in the Kilodegree Extremely Little Telescope (KELT) survey. Of these, 376 are new Mira-like detections. We used Two Micron All Sky Survey (2MASS) colors to identify candidate asymptotic giant branch stars. We searched for photometric variability among the candidate asymptotic giant branch stars and identified stars that show periodic variability. We selected variables with high amplitudes and strong periodic behavior using a Random Forest classifier. Of the sample of 4132 Mira-like variables, we estimate that 70% are Miras and 30% are semiregular (SR) variables. We also adopt the method of using (W_(RP) - W_(K)) versus (J - K_s) colors in distinguishing between O-rich and C-rich Miras and find it to be an improvement over 2MASS colors.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3847/1538-4365/ab6bdbDOIArticle
https://arxiv.org/abs/2001.06498arXivDiscussion Paper
ORCID:
AuthorORCID
Arnold, R. Alex0000-0002-3593-0836
McSwain, M. Virginia0000-0002-4775-2803
Pepper, Joshua0000-0002-3827-8417
Whitelock, Patricia A.0000-0002-4678-4432
Hernitschek, Nina0000-0003-1681-0430
James, David J.0000-0001-5160-4486
Kuhn, Rudolf B.0000-0002-4236-9020
Lund, Michael B.0000-0003-2527-1598
Rodriguez, Joseph E.0000-0001-8812-0565
Siverd, Robert J.0000-0001-5016-3359
Stassun, Keivan G.0000-0002-3481-9052
Additional Information:© 2020. The American Astronomical Society. Received 2019 June 25; revised 2019 December 20; accepted 2020 January 13; published 2020 March 16. We are grateful to the anonymous referee and the AAS statistics consultant for their comments that significantly improved this manuscript. We would like to thank Shazrene Mohamed for her input on the early stages of this work, and R.A.A. thanks Annika Ewigleben and Alyssa Hanes for constructive criticism of the manuscript. R.A.A. was supported by the NSF grants PHY-0849416 and PHY-1359195. R.A.A. would like to acknowledge support from Lehigh University, specifically financial support through the Doctoral Travel Grant for Global Opportunities and the Summer Research Fellowship from the College of Arts and Sciences, and support from the Department of Physics. R.A.A. would also like to acknowledge support from the IAU in the form of a travel grant. M.V.M. was supported by a Dean's Associate Professor Advancement Fellowship from Lehigh University. P.A.W. acknowledges research funding from the South African NRF. This research has made use of the SIMBAD database and the VizieR catalog access tool, both operated at CDS, Strasbourg, France, and the International Variable Star Index (VSX) database, operated at AAVSO, Cambridge, Massachusetts, USA. We have also made use of Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013, 2018); NumPy (van der Walt et al. 2011); Scikit-Learn (Pedregosa et al. 2012); and Matplotlib, a Python library for publication quality graphics (Hunter 2007). 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, https://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.
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
NSFPHY-0849416
NSFPHY-1359195
Lehigh UniversityUNSPECIFIED
International Astronomical UnionUNSPECIFIED
National Research Foundation (South Africa)UNSPECIFIED
Gaia Multilateral AgreementUNSPECIFIED
Subject Keywords:Mira variable stars ; Long period variable stars ; Time series analysis
Issue or Number:2
Classification Code:Unified Astronomy Thesaurus concepts: Mira variable stars (1066); Long period variable stars (935); Time series analysis (1916)
Record Number:CaltechAUTHORS:20200316-150528185
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200316-150528185
Official Citation:R. Alex Arnold et al 2020 ApJS 247 44
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101924
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:17 Mar 2020 15:01
Last Modified:17 Mar 2020 15:01

Repository Staff Only: item control page