Year: 2025
Type: article
Abstract: 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 $=9\times 10^{-10}$), however this can be plausibly accounted for by including the effects of cosmological surface brightness dimming and the passive ageing 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.
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,046
Funders: Princeton University, Leverhulme Trust, Ministry of Education, Culture, Sports, Science and Technology, University of New South Wales, Academia Sinica, Cabinet Office, Government of Japan, National Astronomical Observatory of Japan, High Energy Accelerator Research Organization, Toray Science Foundation, Science and Technology Facilities Council, Australian Research Council, Japan Society for the Promotion of Science, Japan Science and Technology Agency, Agencia Estatal de Investigación, European Social Fund
Awards: G2262748287, G3480869486, G4065643129, G425668148, G4653484084, G4655338613, 原子炉による悪性皮膚腫瘍の選択的治療, G5080475149, G617610489, G6218905885, G6996428894, G7084143925, 古代説話における諸寺縁起の研究, Unveiling the hidden stars of the Universe, Astronomy and Astrophysics at the University of Nottingham - 2023 to 2026
OpenAlex ID: W4417156352
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