Challenges of standard halo models in constraining galaxy properties from CIB anisotropies

Abstract

The halo model, combined with halo occupation distribution (HOD) prescriptions, is widely used to interpret cosmic infrared background (CIB) anisotropies and connect star-forming galaxies to large-scale structure. Recent implementations adopt more physical parameterizations, but it remains unclear whether these models reliably recover astrophysical quantities. We test whether current CIB halo models can constrain the star formation efficiency, $\eta (M_h,z)$, and the halo mass where it peaks, $M_{\max }$, when fitted to mock data. We examine whether discrepancies arise from emission assumptions (the HOD ingredients) or from more fundamental components, such as bias and matter clustering. Using the M21 CIB HOD model within the halo framework, we fit mock CIB power spectra and star formation rate density (SFRD) data from the SIDES-Uchuu simulation, then repeat the analysis with a simplified simulation (SSU) matched to the HOD assumptions. Comparing best-fit parameters to known inputs, we find that although the M21 model fits the mock data well, it fails to recover intrinsic parameters, especially $M_{\max }$, even when applied to data generated with consistent assumptions. Emission-related quantities (SFRD, emissivity) agree within 5%, but the two-halo term shows a redshift- and scale-dependent offset exceeding 20%, likely due to the linear treatment of halo bias and matter clustering. Scatter in the SFR-halo mass relation and spectral energy distributions significantly impacts shot noise ($\sim 50\%$) but only modestly ($<10\%$) the clustered signal. We conclude that robust recovery of physical parameters from CIB clustering requires improved cosmological ingredients in halo models, including scale-dependent halo bias and nonlinear matter power spectra, alongside refined emission modeling.

References in corpus (20)

• Cosmic Star Formation History
• The Herschel view of the dominant mode of galaxy growth from z=4 to the present day
• HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback
• Evolution of the dust emission of massive galaxies up to z=4 and constraints on their dominant mode of star formation
• The ALPINE-ALMA [CII] Survey: Obscured Star Formation Rate Density and Main Sequence of star-forming galaxies at z>4
• Correlated Anisotropies in the Cosmic Far-Infrared Background Detected by MIPS/Spitzer: Constraint on the Bias
• CONCERTO: High-fidelity simulation of millimeter line emissions of galaxies and [CII] intensity mapping
• Inferring the Redshift Distribution of the Cosmic Infrared Background
• KiDS-1000: Combined halo-model cosmology constraints from galaxy abundance, galaxy clustering and galaxy-galaxy lensing
• Including beyond-linear halo bias in halo models
• Precision Tests of CO and [CII] Power Spectra Models against Simulated Intensity Maps
• A scale dependent bias on linear scales: the case for HI intensity mapping at z=1
• Improving models of the cosmic infrared background using CMB lensing mass maps
• Revisiting the [C II]${}_{158\mu \text{m}}$ line-intensity mapping power spectrum from the EoR using non-uniform line-luminosity scatter
• The halo model with beyond-linear halo bias: unbiasing cosmological constraints from galaxy-galaxy lensing and clustering
• The star formation history in the last 10 billion years from CIB cross-correlations
• The BAHAMAS project: Evaluating the accuracy of the halo model in predicting the non-linear matter power spectrum
• The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective
• Scatter in the star formation rate-halo mass relation: secondary bias and its impact on line-intensity mapping
• A halo model approach to describe clustering and emission of the two main star forming galaxy populations for Cosmic Infrared Background studies