Search for Galaxy Cluster Candidates in the Cosmic Microwave Background Maps of the Planck Space Mission Using a Convolutional Neural Network Based on the Method of Tracing the Sunyaev–Zeldovich Effect

Abstract—We propose a method of searching for radio sources exhibiting the Sunyaev–Zeldovich effect in multi-frequency emission maps from Planck mission data using convolutional neural network. A catalog recognizing is compiled GLESP pixelation scheme at frequencies 100, 143, 217, 353, and 545 GHz. The quality proposed approach evaluated dependence model on S/N ratio estimated. We show that presented network allows detection with effect. can be used to find most likely galaxy cluster candidates large redshifts.