Detecting short period variable stars with Gaia

TL;DR

This study evaluates Gaia's ability to detect and accurately recover short period variable stars, specifically ZZ Ceti stars, through simulated light curves and Fourier analysis, demonstrating a 65% success rate in period recovery.

Contribution

The paper presents a simulation-based assessment of Gaia's performance in detecting short period ZZ Ceti variables, highlighting the potential and limitations of Gaia's data for these stars.

Findings

Correct period recovery in ~65% of cases for G ~ 18 magnitude stars

Second period also recovered in ~26% of cases

Gaia's sampling and precision enable effective detection of short period variables

Abstract

We analyzed the frequency domain of time series of simulated ZZ Ceti light-curves to investigate the detectability and period recovery performance of short period variables (periods < 2 hours) for the Gaia mission. In our analysis, first we used a non-linear ZZ Ceti light-curves simulator code to simulate the variability of ZZ Ceti stars (we assumed stationary power spectra over five years). Second we used the Gaia nominal scanning law and the expected photometric precision of Gaia to simulate ZZ Ceti time series with Gaia's time sampling and photometric errors. Then we performed a Fourier analysis of these simulated time series. We found that a correct period can be recovered in ~65% of the cases if we consider Gaia per CCD time series of a G ~ 18 magnitude multiperiodic ZZ Ceti star with 5%-10% light-curve variation. In the pre-whitened power spectrum a second correct period was also recovered in ~26% of the cases.