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Dark matter density profiles in dwarf galaxies: linking Jeans modelling systematics and observation

Chang, Laura J. and Necib, Lina (2021) Dark matter density profiles in dwarf galaxies: linking Jeans modelling systematics and observation. Monthly Notices of the Royal Astronomical Society, 507 (4). pp. 4715-4733. ISSN 0035-8711. doi:10.1093/mnras/stab2440.

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The distribution of dark matter in dwarf galaxies can have important implications on our understanding of galaxy formation as well as the particle physics properties of dark matter. However, accurately characterizing the dark matter content of dwarf galaxies is challenging due to limited data and complex dynamics that are difficult to accurately model. In this paper, we apply spherical Jeans modelling to simulated stellar kinematic data of spherical, isotropic dwarf galaxies with the goal of identifying the future observational directions that can improve the accuracy of the inferred dark matter distributions in the Milky Way dwarf galaxies. We explore how the dark matter inference is affected by the location and number of observed stars as well as the line-of-sight velocity measurement errors. We use mock observation to demonstrate the difficulty in constraining the inner core/cusp of the dark matter distribution with data sets of fewer than 10 000 stars. We also demonstrate the need for additional measurements to make robust estimates of the expected dark matter annihilation signal strength. For the purpose of deriving robust indirect detection constraints, we identify Ursa Major II, Ursa Minor, and Draco as the systems that would most benefit from additional stars being observed.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Chang, Laura J.0000-0001-8590-2043
Necib, Lina0000-0003-2806-1414
Additional Information:© 2021 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Accepted 2021 August 20. Received 2021 August 13; in original form 2020 September 28. Published: 27 August 2021. We are particularly grateful to M. Geha and M. Lisanti for their helpful insight on the topic. We also thank P. Hopkins, A. Ji, E. Kirby, J. Read, J. Simon, and M. Walker for helpful discussions. LJC thanks S. Mishra-Sharma for fruitful discussions and moral support. LJC is supported by a Paul & Daisy Soros Fellowship and an NSF Graduate Research Fellowship under Grant Number DGE-1656466. LN is supported by the DOE under Award Number DESC0011632, the Sherman Fairchild fellowship, the University of California Presidential Fellowship, and a Carnegie Fellowship in Theoretical Astrophysics. The work presented in this paper was performed on computational resources managed and supported by Princeton Research Computing, a consortium of groups including the Princeton Institute for Computational Science and Engineering (PICSciE) and the Office of Information Technology’s High Performance Computing Center and Visualization Laboratory at Princeton University. Data Availability: The simulated data sets underlying this article were generated using the public code STARSAMPLER using the parameters described in the article, and will be shared on reasonable request to the authors.
Group:Walter Burke Institute for Theoretical Physics
Funding AgencyGrant Number
Paul and Daisy Soros FellowshipUNSPECIFIED
NSF Graduate Research FellowshipDGE-1656466
Department of Energy (DOE)DESC0011632
Sherman Fairchild FoundationUNSPECIFIED
University of CaliforniaUNSPECIFIED
Subject Keywords:galaxies: dwarf – (cosmology:) dark matter – gamma-rays: galaxies
Issue or Number:4
Record Number:CaltechAUTHORS:20211026-212504430
Persistent URL:
Official Citation:Laura J Chang, Lina Necib, Dark matter density profiles in dwarf galaxies: linking Jeans modelling systematics and observation, Monthly Notices of the Royal Astronomical Society, Volume 507, Issue 4, November 2021, Pages 4715–4733,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:111650
Deposited By: Tony Diaz
Deposited On:26 Oct 2021 21:46
Last Modified:26 Oct 2021 21:46

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