Einasto profile as the halo model solution coupled to the depletion radius

TL;DR

This paper develops a method to determine halo profiles outside their boundaries by solving linear equations in Fourier space, demonstrating that the Einasto profile coupled with the depletion radius provides accurate power spectrum predictions.

Contribution

It introduces a novel approach to match halo profiles to observed power spectra using the halo model, highlighting the effectiveness of the Einasto profile with the depletion radius boundary.

Findings

Matching profiles can accurately reconstruct matter statistics.

Inner depletion radii profiles are consistent across catalogs.

Einasto profile with depletion radius predicts power spectra within 10%.

Abstract

We constrain the halo profiles outside the halo boundaries by solving for the matching profiles required by the halo model. In the halo model framework, the matter distribution in the universe can be decomposed into the spatial distribution of halos convolved with their internal structures. This leads to a set of linear equations in Fourier space which uniquely determines the matching halo profiles for any given halo catalog. In this work, we construct three halo catalogs with different boundary definitions, and solve for the matching profiles in each case using measurements of halo-matter and halo-halo power spectra. Our results show that for a given halo field, there is always a set of matching profiles to accurately reconstruct the input statistics of the matter field, even though it might be complex to model the profiles analytically. Comparing the solutions from different halo catalogs, we find their mass distributions inside the inner depletion radii are nearly identical, while they deviate from each other on larger scales, with a larger boundary resulting in a more extended profile. For the depletion radius based catalog, the numerical solution agrees well with the Einasto profile. Coupling the Einasto profile with the depletion catalog, the resulting halo model can simultaneously predict the halo-matter power spectra to $10\%$ and matter-matter power spectrum to $5\%$, improving over conventional models in both the interpretability and versatility. The conditions and limitation of using the Navarro-Frenk-White profile in the halo model are also discussed.