2025/12/04 by Louisa Canepa, Canepa, Louisa, Sarah Brough +5
Engineering · Physics and Astronomy · #Astronomy and Astrophysical Research #Astrophysics of Galaxies (astro-ph.GA) #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Space Technology and Applications
paper · pdf · doi:10.48550/arxiv.2512.05187
openalex publication_date 2025/12/04 · openalex created_date 2025/12/09 · openalex updated_date 2026/07/28
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 rS=-0.604, p-value =9×10-10), 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 (rS=-0.330, p-value =8× 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 (rS=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.