ICM-SHOX. Paper I: Methodology overview and discovery of a gas--dark matter velocity decoupling in the MACS J0018.5+1626 merger
Emily M. Silich, Elena Bellomi, Jack Sayers, John ZuHone, Urmila, Chadayammuri, Sunil Golwala, David Hughes, Alfredo Monta\~na, Tony, Mroczkowski, Daisuke Nagai, David S\'anchez, S. A. Stanford, Grant Wilson,, Michael Zemcov, Adi Zitrin

TL;DR
This paper introduces ICM-SHOX, a comprehensive framework combining multi-probe observations and hydrodynamical simulations to analyze galaxy cluster mergers, revealing a velocity decoupling between gas and dark matter in MACS J0018.5+1626.
Contribution
The paper presents a novel systematic pipeline, ICM-SHOX, for constraining merger parameters and discovering velocity decoupling in galaxy clusters through multi-probe data and simulations.
Findings
Constrained the merger epoch to 0-60 Myr post-pericenter.
Identified a velocity decoupling between gas and dark matter distributions.
Estimated impact parameter, mass ratio, and initial velocity of the merger.
Abstract
Galaxy cluster mergers are rich sources of information to test cluster astrophysics and cosmology. However, cluster mergers produce complex projected signals that are difficult to interpret physically from individual observational probes. Multi-probe constraints on the gas and dark matter cluster components are necessary to infer merger parameters that are otherwise degenerate. We present ICM-SHOX (Improved Constraints on Mergers with SZ, Hydrodynamical simulations, Optical, and X-ray), a systematic framework to jointly infer multiple merger parameters quantitatively via a pipeline that directly compares a novel combination of multi-probe observables to mock observables derived from hydrodynamical simulations. We report a first application of the ICM-SHOX pipeline to MACS J0018.5+1626, wherein we systematically examine simulated snapshots characterized by a wide range of initial…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Adaptive optics and wavefront sensing · Statistical and numerical algorithms
