Weighing gas-rich starless halos: Dark matter parameter inference based on gas distributions

Context. Reionization-limited H I clouds (RELHICs) are starless dark matter halos that retain 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. Aims. In this work 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. Methods. Using RELHICs from a redshift z = 0 high-resolution cosmological hydrodynamical simulation, we employed Bayesian nested sampling to infer dark matter halo mass and concentration. We evaluated this approach against 3D spherically averaged total gas and H I density profiles alongside 2D H I column density profiles. Results. 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, and underdense regions show the inverse. Consequently, detectable low-mass systems are biased toward higher masses and lower concentrations. Applying this to 2D projected H I column densities washes out radial features via line-of-sight integration, which preserves mass constraints but exacerbates concentration underestimation. Conclusions. The local intergalactic medium modulates the RELHIC gas content, meaning universal boundary conditions force artificial adjustments to the inferred halo parameters to compensate for external pressure. 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.