Weighing gas-rich starless halos: dark matter parameters inference from their gas distributions
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
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2026
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| _version_ | 1866918500510990336 |
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| author | Turini, Francesco Benitez-Llambay, Alejandro |
| author_facet | Turini, Francesco Benitez-Llambay, Alejandro |
| contents | Reionization-Limited $H_{I}$ Clouds (RELHICs) are starless dark matter halos retaining a significant neutral hydrogen($H_{I}$ ) reservoir. The gas resides in near hydrostatic equilibrium within the dark matter potential and in thermal equilibrium with the cosmic ultraviolet background. This simplicity allows analytic frameworks to link observable $H_{I}$ column densities directly to fundamental dark matter halo structural parameters. We systematically assess the accuracy of inferring host halo parameters from RELHIC gas distributions on an object-by-object basis, quantifying biases, intrinsic degeneracies, and the limits of parameter recovery. Using RELHICs from a redshift z = 0 high-resolution cosmological hydrodynamical simulation, we employ Bayesian nested sampling to infer dark matter halo mass and concentration. We evaluate this against 3D spherically averaged total gas and $H_{I}$ density profiles, alongside 2D $H_{I}$ column density profiles. We found that while the ensemble inference yields a robust, unbiased recovery of halo virial mass from 3D profiles, individual systems exhibit a mass-concentration degeneracy driven by local environmental density. Overdense environments yield slightly overestimated masses and underestimated concentrations; underdense regions show the inverse. We demonstrate that treating environmental density as a free parameter breaks this degeneracy and completely neutralizes the systematic mass bias. Although concentration recovery remains limited by simulation resolution, the virial mass is exceptionally well constrained, establishing a highly reliable framework for weighing starless halos in upcoming surveys. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05597 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Weighing gas-rich starless halos: dark matter parameters inference from their gas distributions Turini, Francesco Benitez-Llambay, Alejandro Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics Reionization-Limited $H_{I}$ Clouds (RELHICs) are starless dark matter halos retaining a significant neutral hydrogen($H_{I}$ ) reservoir. The gas resides in near hydrostatic equilibrium within the dark matter potential and in thermal equilibrium with the cosmic ultraviolet background. This simplicity allows analytic frameworks to link observable $H_{I}$ column densities directly to fundamental dark matter halo structural parameters. We systematically assess the accuracy of inferring host halo parameters from RELHIC gas distributions on an object-by-object basis, quantifying biases, intrinsic degeneracies, and the limits of parameter recovery. Using RELHICs from a redshift z = 0 high-resolution cosmological hydrodynamical simulation, we employ Bayesian nested sampling to infer dark matter halo mass and concentration. We evaluate this against 3D spherically averaged total gas and $H_{I}$ density profiles, alongside 2D $H_{I}$ column density profiles. We found that while the ensemble inference yields a robust, unbiased recovery of halo virial mass from 3D profiles, individual systems exhibit a mass-concentration degeneracy driven by local environmental density. Overdense environments yield slightly overestimated masses and underestimated concentrations; underdense regions show the inverse. We demonstrate that treating environmental density as a free parameter breaks this degeneracy and completely neutralizes the systematic mass bias. Although concentration recovery remains limited by simulation resolution, the virial mass is exceptionally well constrained, establishing a highly reliable framework for weighing starless halos in upcoming surveys. |
| title | Weighing gas-rich starless halos: dark matter parameters inference from their gas distributions |
| topic | Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2603.05597 |