A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

Klein, M and Desai, Shantanu and et al, . (2018) A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets. Monthly Notices of the Royal Astronomical Society, 474 (3). pp. 3324-3343. ISSN 0035-8711

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Abstract

We describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF–redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity–λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF–mass relation.

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