Systematic evaluation of variability detection methods for eROSITA

The reliability of detecting source variability in sparsely and irregularly sampled X-ray light curves is investigated. This is motivated by the unprecedented survey capabilities of eROSITA on board the Spektrum-Roentgen-Gamma observatory, providing light curves for many thousand sources in its final-depth equatorial deep-field survey. Four methods for detecting variability are evaluated: excess variance, amplitude maximum deviations, Bayesian blocks, and a new Bayesian formulation of the excess variance. We judge the false-detection rate of variability based on simulated Poisson light curves of constant sources, and calibrate significance thresholds. Simulations in which flares are injected favour the amplitude maximum deviation as most sensitive at low false detections. Simulations with white and red stochastic source variability favour Bayesian methods. The results are applicable also for the million sources expected in the eROSITA all-sky survey