Evidence for substructure in Ursa Minor dwarf spheroidal galaxy using a Bayesian object detection method
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2014Metadata
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Pace, Andrew B.
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Evidence for substructure in Ursa Minor dwarf spheroidal galaxy using a Bayesian object detection method
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 4.25 ± 0.75 km s−1 and centred at
(9.1 arcmin ± 1.5, 7.2 arcmin ± 1.2) in relative RA and Dec. with respect to the centre of
Ursa Minor. The second object has a large velocity offset of −12.8+1.75
−1.5 km s−1 compared
to Ursa Minor and centred at (−14.0 arcmin+2.4
−5.8,−2.5 arcmin+0.4
−1.0). 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 2.0 kms−1 at 95 per cent confidence level differs from
previous work. We use two- and three-component models along with the information criteria
and Bayesian evidence model selection methods to argue that Ursa Minor has additional
localized secondary populations. The significant probability for a large velocity dispersion in
each secondary object raises the intriguing possibility that each has its own dark matter halo,
that is, it is a satellite of a satellite of the Milky Way.
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This researchwas supported in part by the National Science Foundation
Grant 0855462 atUCIrvine. This researchwas supported in part
by the Perimeter Institute of Theoretical Physics during a visit by
MK.Research at Perimeter Institute is supported by the Government
of Canada through Industry Canada and by the Province of Ontario
through the Ministry of Economic Development and Innovation.
GDM acknowledges support from the Wenner-Gren Foundations.
RRM acknowledges support from the GEMINI-CONICYT Fund,
allocated to the project no. 32080010, from CONICYT through
project BASAL PFB-06, and the Fondo Nacional de Investigaci´on
Cient´ıfica y Tecnol´ogica (Fondecyt project no. 1120013).
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MNRAS 442, 1718–1730 (2014)
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