Modelling and Subtracting Diffuse Cluster Light in JWST Images: A Relation between the Spatial Distribution of Globular Clusters, Dwarf Galaxies, and Intracluster Light in the Lensing Cluster SMACS 0723
Nicholas S. Martis, Ghassan T. E. Sarrouh, Chris J. Willott, Roberto, Abraham, Yoshihisa Asada, Maru\v{s}a Brada\v{c}, Gabe Brammer, Anishya, Harshan, Adam Muzzin, Ga\"el Noirot, Marcin Sawicki, Gregor Rihtar\v{s}i\v{c}

TL;DR
This paper introduces a method to model and subtract diffuse light in JWST images of galaxy clusters, revealing that globular clusters and intracluster light share a common origin, and demonstrating their spatial correlation with dark matter.
Contribution
The study develops a novel technique for removing galaxy and ICL light in JWST images, enabling detailed analysis of globular clusters and dwarf galaxies in clusters.
Findings
Globular clusters trace the diffuse intracluster light.
Dwarf galaxies are concentrated near the cluster center.
Strong correlation between compact source density and total cluster light.
Abstract
We present a methodology for modeling and removing light from cluster galaxies and intracluster light (ICL) from () images of gravitational lensing clusters. We apply our method to Webb's First Deep Field the SMACS 0723 Early Release Observations and use the ICL subtracted images to select a sample of globular clusters (GCs) and dwarf galaxies within the cluster. We compare the spatial distributions of these two samples with our models of the galaxy and ICL light, finding significant similarity. Specifically we find that GCs trace the diffuse ICL, while dwarf galaxies are centrally concentrated near the cluster center We quantify the relationship between the surface density of compact sources and total cluster light, demonstrating a significant, tight correlation. We repeat our methodology and compare distributions of GCs with dark matter surface…
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Taxonomy
TopicsAdaptive optics and wavefront sensing · Astronomy and Astrophysical Research · Stellar, planetary, and galactic studies
