Recovering variable stars in large surveys: EA_(up) Algol-type class in the Catalina Survey
Abstract
The discovery and characterization of Algol eclipsing binaries (EAs) provide an opportunity to contribute for a better picture of the structure and evolution of low-mass stars. However, the cadence of most current photometric surveys hinders the detection of EAs since the separation between observations is usually larger than the eclipse(s) duration and hence few measurements are found at the eclipses. Even when those objects are detected as variable, their periods can be missed if an appropriate oversampling factor is not used in the search tools. In this paper, we apply this approach to find the periods of stars catalogued in the Catalina Real-Time Transient Survey (CRTS) as EAs having unknown period (EA_(up)). As a result, the periods of ∼56percent of them were determined. Eight objects were identified as low-mass binary systems and modelled with the Wilson & Devinney synthesis code combined with a Markov chain Monte Carlo optimization procedure. The computed masses and radii are in agreement with theoretical models and show no evidence of inflated radii. This paper is the first of a series aiming to identify suspected binary systems in large surveys.
Additional Information
© 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2020 August 13. Received 2020 July 26; in original form 2019 December 26. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. CEFL acknowledges a post-doctoral fellowship from the CNPq. NJGC acknowledges support from the UK Science and Technology Facilities Council. The authors thank to MCTIC/FINEP (CT-INFRA grant 0112052700) and the Embrace Space Weather Program for the computing facilities at INPE. CVR thanks the grant #2013/26258-4 from São Paulo Research Foundation (FAPESP) and CNPq (Proc. 303444/2018-5). Support for AP and MC is provided by Proyecto Basal AFB-170002; by the Chilean Ministry for the Economy, Development, and Tourism's Millennium Science Initiative through grant IC 120009, awarded to the Millennium Institute of Astrophysics (MAS); and by FONDECYT project #1171273. DATA AVAILABILITY. The data underlying this paper are available in the paper and in its online supplementary material.Attached Files
Published - staa2518.pdf
Submitted - 2008.07306.pdf
Files
Name | Size | Download all |
---|---|---|
md5:b84562438301b4de7945b5ce87543c11
|
2.8 MB | Preview Download |
md5:f8ff450a716ccacd1a91393e57f57b70
|
5.4 MB | Preview Download |
Additional details
- Alternative title
- Recovering variable stars in large surveys: EAup Algol-type class in the Catalina Survey
- Eprint ID
- 106930
- Resolver ID
- CaltechAUTHORS:20201204-161632730
- 001
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
- 303444/2018-5
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
- Science and Technology Facilities Council (STFC)
- 0112052700
- Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC)
- 2013/26258-4
- Fundação de Amparo à Pesquisa do Estado de Sao Paulo (FAPESP)
- AFB-170002
- BASAL-CATA
- IC 120009
- Iniciativa Científica Milenio del Ministerio de Economía, Fomento y Turismo
- 1171273
- Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT)
- Created
-
2020-12-05Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field