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Title: DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS
Abstract The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg2tog∼ 24.0 and ∼27,700 deg2tog∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣b∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of 26 5 47 + 79 satellite galaxies with −20 ≤MV≤ 0, half-light radii of 15 ≤r1/2, (pc) ≤ 3000, and galactocentric distances of 10 ≤DGC(kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2σ, which can be attributed to the clustering of satellites associated with the LMC.  more » « less
Award ID(s):
2508745
PAR ID:
10687743
Author(s) / Creator(s):
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Corporate Creator(s):
Publisher / Repository:
Astrophysical Journal
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
1000
Issue:
1
ISSN:
0004-637X
Page Range / eLocation ID:
87
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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