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arXiv · 2503.04098

A Detection of Circumgalactic Dust at Megaparsec Scales with Maximum Likelihood Estimation

Abstract

One of the more surprising astrophysical discoveries of the last decade has been the presence of enormous quantities of dust at megaparsec distances from galaxies, which has important implications for galaxy evolution, the circumgalactic and intergalactic medium, and observational cosmology. In this work, we present a novel method for studying these vast halos of circumgalactic dust: a maximum-likelihood estimator for dust-induced extinction of background galaxies. This estimator can accommodate a broad range of archival photometric data and can incorporate different dust reddening prescriptions, making it applicable to diverse galaxy types and redshifts. We apply the estimator to the redMaGiC catalog of luminous red galaxies, selected for their tight dispersion in color and well-constrained photometric redshifts, and measure the resulting extinction as a function of projected distance from WISExSuperCOSMOS and redMaGiC foreground galaxies. We detect significant dust-induced extinction profiles extending to at least 1 megaparsec from galactic disks, with noticeable differences between star-forming and quiescent galaxies: star-forming galaxies exhibit a pronounced rise in extinction within the inner 50 kiloparsecs and a steep decline beyond 1 megaparsec, while the quiescent galaxies host little dust in the inner halo but have detectable extinction out to 30 megaparsecs. We test the robustness of our results using star catalogs and inverted foreground and background samples and find no evidence for significant systematic error. Our approach provides a powerful tool for studying the interplay between circumgalactic dust, galaxy evolution, and large-scale structure, with potential applications in a number of astrophysical subfields.

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BibTeXRIS

Jacqueline E. McCleary, Eric M. Huff, James W. Bartlett, Brandon S. Hensley. 2026-02-23. A Detection of Circumgalactic Dust at Megaparsec Scales with Maximum Likelihood Estimation. https://arxiv.org/abs/2503.04098

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