To β or not to β: can higher order Jeans analysis break the mass-Anisotropy degeneracy in simulated dwarfs?

A. Genina, J. I. Read, C. S. Frenk, S. Cole, A. Benítez-Llambay, A. D. Ludlow, J. F. Navarro, K. A. Oman, A. Robertson

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We test a non-parametric higher order Jeans analysis method, GravSphere, on 32 simulated dwarf galaxies comparable to classical Local Group dwarfs like Fornax. The galaxies are selected from A Project Of Simulating The Local Environment (APOSTLE) suite of cosmological hydrodynamics simulations with cold dark matter (CDM) and self-interacting dark matter (SIDM) models, allowing us to investigate cusps and cores in density distributions. We find that, for CDM dwarfs, the recovered enclosed mass profiles have a bias of no more than 10 per cent, with a 50 per cent scatter in the inner regions and a 20 per cent scatter near the half-light radius, consistent with standard mass estimators. The density profiles are also recovered with a bias of no more than 10 per cent and a scatter of 30 per cent in the inner regions. For SIDM dwarfs, the mass and density profiles are recovered within our 95 per cent confidence intervals but are biased towards cuspy dark matter distributions. This is mainly due to a lack of sufficient constraints from the data. We explore the sources of scatter in the accuracy of the recovered profiles and suggest a χ2 statistic to separate successful models from biased ones. Finally, we show that the uncertainties on the mass profiles obtained with GravSphere are smaller than those for comparable Jeans methods and that they can be further improved if stronger priors, motivated by cosmological simulations, are placed on the velocity anisotropy. We conclude that GravSphere is a promising Jeans-based approach for modelling dark matter distributions in dwarf galaxies.

Original languageEnglish
Pages (from-to)144-163
Number of pages20
JournalMonthly Notices of the Royal Astronomical Society
Volume498
Issue number1
DOIs
Publication statusPublished - 1 Oct 2020

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