Evidence for Substructure in Ursa Minor Dwarf Spheroidal Galaxy using a Bayesian Object Detection Method
Andrew B. Pace (1), Gregory D. Martinez (1,2), Manoj Kaplinghat (1),, Ricardo R. Mu\~noz (3, 4), ((1) Center for Cosmology, Department of Physics, and Astronomy, University of California, Irvine, (2) The Oskar Klein Center,, Department of Physics, Stockholm University

TL;DR
This paper introduces a Bayesian method to detect localized stellar populations in dwarf galaxies, revealing substructures in Ursa Minor that suggest complex dark matter distributions and satellite interactions.
Contribution
The paper develops a Bayesian object detection technique and applies it to Ursa Minor, identifying multiple secondary populations with implications for dark matter and galaxy formation.
Findings
Identified two secondary objects in Ursa Minor with distinct kinematic properties.
Found evidence that these objects may have their own dark matter halos.
Demonstrated the effectiveness of Bayesian model selection in astrophysical substructure detection.
Abstract
We present a method for identifying localized secondary populations in stellar velocity data using Bayesian statistical techniques. We apply this method to the dwarf spheroidal galaxy Ursa Minor and find two secondary objects in this satellite of the Milky Way. One object is kinematically cold with a velocity dispersion of and centered at in relative RA and DEC with respect to the center of Ursa Minor. The second object has a large velocity offset of compared to Ursa Minor and centered at . The kinematically cold object has been found before using a smaller data set but the prediction that this cold object has a velocity dispersion larger than at 95% C.L. differs from previous work. We use two and three component models along…
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