2023/02/27 by S. D. Bykov, Bykov, S. D., M. I. Belvedersky +3
Decision Sciences · Engineering · Physics and Astronomy · #Astronomical Observations and Instrumentation #Astrophysical Phenomena and Observations #FOS: Physical sciences #High Energy Astrophysical Phenomena (astro-ph.HE) #Scientific Measurement and Uncertainty Evaluation
paper · pdf · doi:10.48550/arxiv.2302.13689
openalex publication_date 2023/02/27 · openalex created_date 2023/03/03 · openalex updated_date 2026/07/28
We present a method for the optical identification of sources detected in wide-field X-ray sky surveys. We have constructed and trained a neural network model to characterise the photometric attributes of the populations of optical counterparts of X-ray sources and optical field objects. The photometric information processing result is used for the probabilistic cross-match of X-ray sources with optical DESI Legacy Imaging Surveys sources. The efficiency of the method is illustrated using the SRG/eROSITA Survey of Lockman Hole. To estimate the accuracy of the method, we have produced a validation sample based on the Chandra and XMM-Newton catalogues of X-ray sources. The cross-match precision in our method reaches 94% for the entire X-ray catalogue and 97% for sources with a flux F\rm x, 0.5-2>10-14 erg/s/cm2. We discuss the further development of the optical identification model and the steps needed for its application to the SRG/eROSITA all-sky survey data.