Dark matter halo properties from spatially integrated i flux profiles

Journal article

Resolved rotation curves (RCs) are our best probe of the dark matter distribution around individual galaxies. However their acquisition is resource-intensive, rendering them impractical for large-scale surveys and studies at higher redshift. Spatially integrated flux profiles on the other hand are observationally abundant and also probe dynamics across the whole disc. Despite this, they are typically only studied using the highly compressed linewidth summary statistic, discarding much of the available information. Here we construct a Bayesian model to infer halo properties from the full shape of the spatially integrated 21-cm line profile of a galaxy, utilizing all the available information. We validate our model by assessing the consistency of halo parameters obtained from the flux profile with those obtained from RC fits for a sample of 20 galaxies where both are available, finding good agreement provided the profile is not strongly asymmetric. We study the relative constraining power (quantified using the Kullback–Leibler divergence of the posterior from the prior), finding the flux profile inference recovers posteriors on generalized Navarro–Frenk–White halo parameters on average three times tighter than those from the linewidth, and in some cases as tight as those from resolved RCs. Finally we introduce and validate a probabilistic empirical model for the spatial distribution of , enabling our model to be applied to data sets for which no spatially resolved information is available. As the next-generation of observatories comes online, our framework will enable mass modelling in new regimes, with particular utility for constraining the dark matter content of galaxies across cosmic time.

Authors: Yasin, T; Desmond, H

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Monthly Notices of the Royal Astronomical Society
• Volume: 549
• Issue: 4
• Pages: stag574
• Article number: stag574
• Publication date: 2026-03-27
• Acceptance date: 2026-01-10
• DOI: 10.1093/mnras/stag574
• EISSN: 1365-2966
• ISSN: 0035-8711
• Language: English
• Keywords: galaxies: statistics; galaxies: kinematics and dynamics; dark matter