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Title: Uncertainties associated with the backward integration of dwarf satellites using simple parametric potentials
ABSTRACT

In order to backward integrate the orbits of Milky Way (MW) dwarf galaxies, much effort has been invested in recent years to constrain their initial phase-space coordinates. Yet equally important are the assumptions on the potential that the dwarf galaxies experience over time, especially given the fact that the MW is currently accreting the Large Magellanic Cloud (LMC). In this work, using a dark-matter-only zoom-in simulation, we test whether the use of common parametric forms of the potential is adequate to successfully backward integrate the orbits of the subhaloes from their present-day positions. We parametrize the recovered orbits and compare them with those from the simulations. We find that simple symmetric parametric forms of the potential fail to capture the complexities and the inhomogeneities of the true potential experienced by the subhaloes. More specifically, modelling a recent massive accretion like that of the LMC as a sum of two spherical parametric potentials leads to substantial errors in the recovered parameters of the orbits. These errors rival those caused due to (a) a 30 per cent uncertainty in the virial mass of the MW and (b) not modelling the potential of the recently accreted massive satellite. Our work suggests that (i) the uncertainties in the parameters of the recovered orbits of some MW dwarfs may be underestimated and that (ii) researchers should characterize the uncertainties inherent to their choice of integration techniques and assumptions of the potential against cosmological zoom-in simulations of the MW, which include a recently accreted LMC.

 
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Award ID(s):
2007065
NSF-PAR ID:
10364031
Author(s) / Creator(s):
;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
512
Issue:
1
ISSN:
0035-8711
Page Range / eLocation ID:
p. 739-760
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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