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Search for interacting galaxy clusters from SDSS DR-17 employing optimized friend-of-friend algorithm and multi-messenger tracers

Authors :
Oak, Tejas
Paul, Surajit
Oak, Tejas
Paul, Surajit
Publication Year :
2024

Abstract

In the theoretical framework of hierarchical structure formation, galaxy clusters evolve through continuous accretion and mergers of substructures. Cosmological simulations have revealed the best picture of the Universe as a 3-D filamentary network of dark-matter distribution called the cosmic web. Galaxy clusters are found to form at the nodes of this network and are the regions of high merging activity. Such mergers being highly energetic, contain a wealth of information about the dynamical evolution of structures in the Universe. Observational validation of this scenario needs a colossal effort to identify numerous events from all-sky surveys. Therefore, such efforts are sparse in literature and tend to focus on individual systems. In this work, we present an improved search algorithm for identifying interacting galaxy clusters and have successfully produced a comprehensive list of systems from SDSS DR-17. By proposing a set of physically motivated criteria, we classified these interacting clusters into two broad classes, 'merging' and 'pre-merging/postmerging' systems. Interestingly, as predicted by simulations, we found that most cases show cluster interaction along the prominent cosmic filaments of galaxy distribution (i.e., the proxy for DM filaments), with the most violent ones at their nodes. Moreover, we traced the imprint of interactions through multi-band signatures, such as diffuse cluster emissions in radio or X-rays. Although we could not find direct evidence of diffuse emission from connecting filaments and ridges; our catalogue of interacting clusters will ease locating such faintest emissions as data from sensitive telescopes like eROSITA or SKA, becomes accessible<br />Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Society

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1430705755
Document Type :
Electronic Resource