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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Bayesian reconstruction of the Milky Way dark matter distribution

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Autor(es):
Karukes, V, E. ; Benito, M. [1] ; Iocco, F. [2, 1] ; Trotta, R. [3, 4] ; Geringer-Sameth, A. [3]
Número total de Autores: 5
Afiliação do(s) autor(es):
[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
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: Journal of Cosmology and Astroparticle Physics; n. 9 SEP 2019.
Citações Web of Science: 2
Resumo

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)

Processo FAPESP: 16/26288-9 - Matéria escura nas galáxias: da Astrofísica a Física Fundamental
Beneficiário:Ekaterina Karukes
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 16/50006-3 - Bayes in the Milky Way: determining the dark matter profile in our galaxy, a novel approach
Beneficiário:Fabio Iocco
Linha de fomento: Auxílio à Pesquisa - Regular