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The stellar-to-halo mass relation of central galaxies across three orders of halo mass

Published 10 Feb 2026 in astro-ph.GA and astro-ph.HE | (2602.10193v1)

Abstract: The stellar content of galaxies is tightly connected to the mass and growth of their host dark matter halos. Observational constraints on this relation remain limited, particularly for low-mass groups, leaving uncertainties in how galaxies assemble their stars across halo mass scales. Accurately measuring the brightest central galaxy (BCG) stellar-to-halo mass relation (SHMR) over a wide mass range is therefore crucial for understanding galaxy formation and the role of feedback processes. Here we present the SHMR spanning $M_{\rm halo} \sim 10{12}$-$10{15}\,M_\odot$, using halo masses derived from eROSITA eRASS1 X-ray data and BCG stellar masses based on SDSS photometry. By stacking X-ray spectra of optically selected groups, we recover robust average halo gas temperatures for each bin, which are then converted to halo masses via the $M$-$T_X$ relation. We find that the SHMR peaks near $M_{\rm halo} \sim 10{12}\,M_\odot$, with a declining stellar fraction at higher masses. This trend reflects a combination of processes that reduce the efficiency of stellar mass growth in massive halos, such as AGN feedback, reduced cooling efficiency, and the increasing dominance of ex-situ assembly, while halos continue to grow through mergers and accretion. Our measurements are consistent over the full mass range with previous observational studies, including weak lensing, X-ray analyses of individual clusters, and kinematical and dynamical methods. Comparisons with hydrodynamical simulations show good agreement at low masses but reveal significant discrepancies in the normalization at cluster scales, highlighting the sensitivity of BCG stellar growth to feedback prescriptions and halo assembly history. These results provide the first X-ray-based observational SHMR covering three orders of magnitude in halo mass, establish a robust benchmark for testing galaxy formation models.

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