Recovering variable stars in large surveys: EA$_{\rm up}$ Algol-type class in the Catalina Survey

TL;DR

This study develops a method to detect and analyze Algol-type eclipsing binaries in large photometric surveys, overcoming observational cadence limitations to determine their periods and physical parameters.

Contribution

It introduces an oversampling approach to recover periods of EAs in large surveys and models low-mass binaries, providing new insights into their properties.

Findings

Approximately 56% of cataloged EAs had their periods successfully determined.

Eight low-mass binary systems were modeled, showing agreement with theoretical models.

No evidence of inflated radii was found in the modeled systems.

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 cataloged in the Catalina Real-Time Transient Survey (CRTS) as EAs having unknown period (EA$_{\rm up}$). As a result, the periods of $\sim 56\%$ of them were determined. Eight objects were identified as low-mass binary systems and modeled with the Wilson \& Devinney synthesis code combined with a Monte-Carlo Markov Chain 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.