Issue |
A&A
Volume 661, May 2022
The Early Data Release of eROSITA and Mikhail Pavlinsky ART-XC on the SRG mission
|
|
---|---|---|
Article Number | A18 | |
Number of page(s) | 15 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202141099 | |
Published online | 18 May 2022 |
Systematic evaluation of variability detection methods for eROSITA
1
Max Planck Institute for Extraterrestrial Physics,
Giessenbachstrasse,
85741
Garching,
Germany
e-mail: johannes.buchner.acad@gmx.com
2
Dr. Karl Remeis-Observatory and Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg,
Sternwartstr. 7,
96049
Bamberg,
Germany
Received:
15
April
2021
Accepted:
3
December
2021
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.
Key words: methods: data analysis / stars: flare / X-rays: bursts / X-rays: galaxies / galaxies: active
© J. Buchner et al. 2022
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Open Access funding provided by Max Planck Society.
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