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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Bayesian reconstruction of the Milky Way dark matter distribution

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Author(s):
Karukes, V, E. ; Benito, M. [1] ; Iocco, F. [2, 1] ; Trotta, R. [3, 4] ; Geringer-Sameth, A. [3]
Total Authors: 5
Affiliation:
[1] Karukes, E., V, IFT UNESP, R Dr Bento Teobaldo Ferraz 271, Sao Paulo - Brazil
[2] Karukes, E., V, ICTP SAIFR, R Dr Bento Teobaldo Ferraz 271, Sao Paulo - Brazil
[3] Imperial Coll London, Blackett Lab, Imperial Ctr Inference & Cosmol, Phys Dept, Astrophys Grp, Prince Consort Rd, London SW7 2AZ - England
[4] Imperial Coll London, Data Sci Inst, William Penney Lab, London SW7 2AZ - England
Total Affiliations: 4
Document type: Journal article
Source: Journal of Cosmology and Astroparticle Physics; n. 9 SEP 2019.
Web of Science Citations: 2
Abstract

We develop a novel Bayesian methodology aimed at reliably and precisely inferring the distribution of dark matter within the Milky Way using rotation curve data. We identify a subset of the available rotation curve tracers that are mutually consistent with each other, thus eliminating data sets that might suffer from systematic bias. We investigate different models for the mass distribution of the luminous (baryonic) component that bracket the range of likely morphologies. We demonstrate the statistical performance of our method on simulated data in terms of coverage, fractional distance, and mean squared error. Applying it to Milky Way data we measure the local dark matter density at the solar circle rho(0) to be rho(0) = 0.43 +/- 0.02(stat) +/- 0.01(sys) GeV/cm(3), with an accuracy similar to 6%. This result is robust to the assumed baryonic morphology. The scale radius and inner slope of the dark matter profile are degenerate and cannot be individually determined with high accuracy. We show that these results are robust to several possible residual systematic errors in the rotation curve data. (AU)

FAPESP's process: 16/26288-9 - Dark matter in galaxies: from Astrophysics to Fundamental Physics
Grantee:Ekaterina Karukes
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 16/50006-3 - Bayes in the Milky Way: determining the dark matter profile in our galaxy, a novel approach
Grantee:Fabio Iocco
Support type: Regular Research Grants