Sub-structure and merger detection in resolved NIKA Sunyaev-Zel'dovich images of distant clusters
R. Adam, O. Hahn, F. Ruppin, P. Ade, P. Andr\'e, M. Arnaud, I., Bartalucci, A. Beelen, A. Beno\^it, A. Bideaud, N. Billot, O. Bourrion, M., Calvo, A. Catalano, G. Coiffard, B. Comis, A. D'Addabbo, F.-X. D\'esert, S., Doyle, C. Ferrari, J. Goupy, C. Kramer, G. Lagache

TL;DR
This study uses high-resolution tSZ observations and filtering algorithms to detect and analyze sub-structures and merger signatures in distant galaxy clusters, enhancing understanding of their formation and evolution.
Contribution
The paper introduces a method combining structure-enhancement filtering with high-resolution tSZ data to identify ICM sub-structures and merger events in distant clusters, validated with simulations.
Findings
Detection of merger signatures in 3 out of 6 clusters
Identification of pressure gradients and peaks related to mergers
First data release of NIKA cluster sample
Abstract
Sub-structures in the hot gas of galaxy clusters are related to their formation history and to the astrophysical processes at play in the intracluster medium (ICM). The thermal Sunyaev-Zel'dovich (tSZ) effect is directly sensitive to the line-of-sight integrated ICM pressure, and is thus particularly adapted to study ICM sub-structures. We apply structure-enhancement filtering algorithms to high resolution tSZ observations of distant clusters, in order to search for pressure discontinuities, compressions, as well as secondary peaks in the ICM. The same filters are applied to synthetic tSZ images extracted from RHAPSODY-G hydrodynamic simulations, in order to better interpret the extracted features. We also study the noise propagation trough the filters and quantify the impact of systematic effects, point source residuals being identified as the dominant potential contaminant. In 3 of…
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