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  Systematic evaluation of variability detection methods for eROSITA

Buchner, J., Boller, T., Bogensberger, D., Malyali, A., Nandra, K., Wilms, J., et al. (2022). Systematic evaluation of variability detection methods for eROSITA. Astronomy and Astrophysics, 661: A18. doi:10.1051/0004-6361/202141099.

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Buchner, Johannes1, Author           
Boller, Thomas2, Author           
Bogensberger, David1, Author           
Malyali, Adam1, Author           
Nandra, Kirpal1, Author           
Wilms, Joern, Author
Dwelly, Tom1, Author           
Liu, Teng1, Author           
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1High Energy Astrophysics, MPI for Extraterrestrial Physics, Max Planck Society, ou_159890              
2Center for Astrochemical Studies at MPE, MPI for Extraterrestrial Physics, Max Planck Society, ou_1950287              

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 Abstract: 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.

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Language(s): eng - English
 Dates: 2022-05-18
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1051/0004-6361/202141099
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Title: Astronomy and Astrophysics
  Other : Astron. Astrophys.
Source Genre: Journal
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Publ. Info: Les Ulis Cedex A France : EDP Sciences
Pages: - Volume / Issue: 661 Sequence Number: A18 Start / End Page: - Identifier: ISSN: 1432-0746
ISSN: 0004-6361
CoNE: https://pure.mpg.de/cone/journals/resource/954922828219_1