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Discovery of 36 eclipsing EL CVn binaries found by the Palomar Transient Factory

van Roestel, J. and Kupfer, T. and Ruiz-Carmona, R. and Groot, P. J. and Prince, T. A. and Burdge, K. and Laher, R. and Shupe, D. L. and Bellm, E. (2018) Discovery of 36 eclipsing EL CVn binaries found by the Palomar Transient Factory. Monthly Notices of the Royal Astronomical Society, 475 (2). pp. 2560-2590. ISSN 0035-8711. http://resolver.caltech.edu/CaltechAUTHORS:20180329-132609534

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Abstract

We report on the discovery and analysis of 36 new eclipsing EL CVn-type binaries, consisting of a core helium-composition pre-white dwarf (pre-He-WD) and an early-type main-sequence companion. This more than doubles the known population of these systems. We have used supervised machine learning methods to search 0.8 million light curves from the Palomar Transient Factory (PTF), combined with Sloan Digital Sky Survey (SDSS), Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) and Two-Micron All-Sky Survey (2MASS) colours. The new systems range in orbital periods from 0.46 to 3.8 d and in apparent brightness from ∼14 to 16 mag in the PTF R or g΄ filters. For 12 of the systems, we obtained radial velocity curves with the Intermediate Dispersion Spectrograph at the Isaac Newton Telescope. We modelled the light curves, radial velocity curves and spectral energy distributions to determine the system parameters. The radii (0.3–0.7 R⊙) and effective temperatures (8000–17 000 K) of the pre-He-WDs are consistent with stellar evolution models, but the masses (0.12–0.28 M⊙) show more variance than models have predicted. This study shows that using machine learning techniques on large synoptic survey data is a powerful way to discover substantial samples of binary systems in short-lived evolutionary stages.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/mnras/stx3291DOIArticle
https://academic.oup.com/mnras/article/475/2/2560/4832486PublisherArticle
https://arxiv.org/abs/1712.06507arXivDiscussion Paper
ORCID:
AuthorORCID
Kupfer, T.0000-0002-6540-1484
Prince, T. A.0000-0002-8850-3627
Laher, R.0000-0003-2451-5482
Bellm, E.0000-0001-8018-5348
Additional Information:© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2017 December 18. Received 2017 December 18; in original form 2017 July 20. Published: 31 January 2018. We thank the referee, Simon Jeffery, for a thorough reading of the manuscript and for providing us with useful comments and suggestions. We thank Adam Miller, Fabian Gieseke and Tom Heskes for many useful discussions about machine learning classification. We thank Tom Marsh for the use of LCURVE. We thank Luc Hendriks for suggesting the use of XGBOOST. JvR acknowledges support from the Netherlands Research School of Astronomy (NOVA) and the Foundation for Fundamental Research on Matter (FOM), and also the California Institute of Technology where a large part of this work was conducted. JvR and PJG thank the University of Cape Town (UCT) for their hospitality; this work was finalized while visiting UCT, supported by the NWO-NRF Bilateral Agreement in Astronomy. This research was supported in part by the National Science Foundation under Grant No. NSF PHY-1125915 and PJG thanks the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara for a productive stay. The Intermediate Palomar Transient Factory project is a scientific collaboration between the California Institute of Technology, Los Alamos National Laboratory, the University of Wisconsin, Milwaukee, the Oskar Klein Center, the Weizmann Institute of Science, the TANGO Program of the University System of Taiwan, and the Kavli Institute for the Physics and Mathematics of the Universe. Funding for the SDSS-IV has been provided by the Alfred P. Sloan Foundation, the US Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org. The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. This publication made use of data products from the 2MASS, 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 Foundation. Based on observations made with the NASA Galaxy Evolution Explorer, which is operated for NASA by the California Institute of Technology under NASA contract NAS5-98034. This publication made use of data products from the WISE, which is a joint project of the University of California, Los Angeles and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France. The original description of the VizieR service was published in A&AS 143, 23. This research has made use of the SVO Filter Profile Service (http://svo2.cab.inta-csic.es/theory/fps/) supported from the Spanish MINECO through grant AyA2014-55216. This research made use of Scikit-learn (Pedregosa et al. 2011). This research made use of ASTROPY, a community-developed core PYTHON package for Astronomy (Robitaille et al. 2013). IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under cooperative agreement with the National Science Foundation (Tody 1993).
Group:Infrared Processing and Analysis Center (IPAC), IPTF
Funders:
Funding AgencyGrant Number
Nederlandse Onderzoekschool Voor Astronomie (NOVA)UNSPECIFIED
Foundation for Fundamental Research on Matter (FOM)UNSPECIFIED
CaltechUNSPECIFIED
NSFPHY-1125915
Alfred P. Sloan FoundationUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Participating InstitutionsUNSPECIFIED
NASANNX08AR22G
NSFAST-1238877
University of MarylandUNSPECIFIED
Eotvos Lorand University (ELTE)UNSPECIFIED
Los Alamos National LaboratoryUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
NASANAS5-98034
NASA/JPL/CaltechUNSPECIFIED
Ministerio de Economía, Industria y Competitividad (MINECO)AyA2014-55216
Subject Keywords:binaries: close – binaries: eclipsing – stars: individual: EL CVn –white dwarfs
Record Number:CaltechAUTHORS:20180329-132609534
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180329-132609534
Official Citation:J van Roestel, T Kupfer, R Ruiz-Carmona, P J Groot, T A Prince, K Burdge, R Laher, D L Shupe, E Bellm; Discovery of 36 eclipsing EL CVn binaries found by the Palomar Transient Factory, Monthly Notices of the Royal Astronomical Society, Volume 475, Issue 2, 1 April 2018, Pages 2560–2590, https://doi.org/10.1093/mnras/stx3291
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85501
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:29 Mar 2018 22:07
Last Modified:29 Mar 2018 22:07

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