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Dark matter profiles of SPARC galaxies: a challenge to fuzzy dark matter

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arxiv 2207.14165 v1 pith:D6XHN7W2 submitted 2022-07-28 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords darkmattergalaxiesfuzzyhalodensitymodelbayesian
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Stellar and gas kinematics of galaxies are a sensitive probe of the dark matter distribution in the halo. The popular fuzzy dark matter models predict the peculiar shape of density distribution in galaxies: specific dense core with sharp transition to the halo. Moreover, fuzzy dark matter predicts scaling relations between the dark matter particle mass and density parameters. In this work, we use a Bayesian framework and several dark matter halo models to analyse the stellar kinematics of galaxies using the Spitzer Photometry and Accurate Rotation Curves database. We then employ a Bayesian model comparison to select the best halo density model. We find that more than half of the galaxies prefer the fuzzy dark model against standard dark matter profiles (NFW, Burkert, and cored NFW). While this seems like a success for fuzzy dark matter, we also find that there is no single value for the particle mass that provides a good fit for all galaxies.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Learning from galactic rotation curves: a neural network approach

    astro-ph.CO 2024-12 conditional novelty 5.0 of 10

    Neural networks trained on simulated rotation curves can infer ultra-light dark matter and baryonic parameters from SPARC dwarf galaxies, with uncertainties comparable to MCMC.

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