The dependence of the intracluster light fraction on galaxy cluster properties

TL;DR

This study uses machine learning on imaging data to analyze how the intracluster light fraction varies with cluster properties like redshift, mass, and relaxation state, revealing correlations that inform ICL formation mechanisms.

Contribution

The paper introduces a machine learning approach to measure ICL fractions across a large sample of galaxy clusters, enabling large-scale trend analysis.

Findings

ICL fraction decreases with redshift, accounting for surface brightness dimming and stellar aging.

Lower mass groups tend to have higher ICL fractions than massive clusters.

Relaxed clusters show marginally higher ICL fractions, supporting galaxy-galaxy interaction formation scenarios.

Abstract

We use machine learning to measure the intracluster light (ICL) fractions of 177 galaxy groups and clusters identified from Hyper Suprime-Cam Subaru Strategic Program imaging to explore how the ICL varies with the properties of its host cluster. We study the variation in ICL fraction with host cluster redshift, halo mass, and magnitude gap to investigate how the ICL develops over time, in various cluster environments, and with cluster relaxation. We find that there is a decreasing correlation with redshift (Spearman correlation $r_S=-0.604$, p-value $=9\times10^{-10}$), however this can be plausibly accounted for by including the effects of cosmological surface brightness dimming and the passive aging of stellar populations. There is a weak negative correlation with halo mass ($r_S=-0.330$, p-value $=8\times 10^{-5}$) where ICL fractions are higher in lower halo mass groups than higher halo mass clusters. We also find that there is a marginal positive correlation with magnitude gap ($r_S=0.226$, p-value = 0.01), indicating that relaxed clusters are more likely to host higher ICL fractions. These results are consistent with a scenario where the dominant formation mechanism of the ICL is galaxy-galaxy interactions such as tidal stripping, and demonstrates the capability of the method to easily construct large samples and study large-scale trends in the ICL fraction.