Algol eclipsing binaries in the Catalina Survey

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 ~56 per cent 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.

Cone search capability for table J/MNRAS/498/2833/tablea1 (Parameters for the iEA stars identified in this work)

Identifier
Source https://dc.g-vo.org/rr/q/lp/custom/CDS.VizieR/J/MNRAS/498/2833
Related Identifier https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/498/2833
Related Identifier http://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/498/2833
Metadata Access http://dc.g-vo.org/rr/q/pmh/pubreg.xml?verb=GetRecord&metadataPrefix=oai_b2find&identifier=ivo://CDS.VizieR/J/MNRAS/498/2833
Provenance
Creator Carmo A.; Ferreira Lopes C.E.; Papageorgiou A.; Jablonski F.J.,Rodrigues C.V.; Drake A.J.; Cross N.J.G.; Catelan M.
Publisher CDS
Publication Year 2023
Rights https://cds.unistra.fr/vizier-org/licences_vizier.html
OpenAccess true
Contact CDS support team <cds-question(at)unistra.fr>
Representation
Resource Type Dataset; AstroObjects
Discipline Astrophysical Processes; Astrophysics and Astronomy; Natural Sciences; Observational Astronomy; Physics; Stellar Astronomy