Light from the Darkness: Detecting Ultra-Diffuse Galaxies in the Perseus Cluster through Over-densities of Globular Clusters with a Log-Gaussian Cox Process
Dayi Li, Gwendolyn M. Eadie, Roberto G. Abraham, Patrick E. Brown,, William E. Harris, Steven R. Janssens, Aaron J. Romanowsky, Pieter van, Dokkum, Shany Danieli

TL;DR
This paper presents a novel statistical method using the log-Gaussian Cox process to detect ultra-diffuse galaxies via globular cluster over-densities, successfully identifying known galaxies and a potential new one in the Perseus cluster.
Contribution
Introduces a new spatial statistical approach for galaxy detection based on globular cluster distributions, applicable to Hubble data, and demonstrates its effectiveness with real and simulated data.
Findings
Successfully detected all known ultra-diffuse galaxies in the survey.
Identified a potential galaxy with no diffuse stellar content.
Detection probability correlates with the number of globular clusters and decreases with larger half-number radius.
Abstract
We introduce a new method for detecting ultra-diffuse galaxies by searching for over-densities in intergalactic globular cluster populations. Our approach is based on an application of the log-Gaussian Cox process, which is a commonly used model in the spatial statistics literature but rarely used in astronomy. This method is applied to the globular cluster data obtained from the PIPER survey, a \textit{Hubble Space Telescope} imaging program targeting the Perseus cluster. We successfully detect all confirmed ultra-diffuse galaxies with known globular cluster populations in the survey. We also identify a potential galaxy that has no detected diffuse stellar content. Preliminary analysis shows that it is unlikely to be merely an accidental clump of globular clusters or other objects. If confirmed, this system would be the first of its kind. Simulations are used to assess how the physical…
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