Semi-analytical frameworks for subhaloes from the smallest to the largest scale

Abstract

Substructures of dark matter halo, called subhalos, provide important clues to understand the nature of dark matter. We construct a useful model to describe the properties of subhalo mass functions based on the well-known analytical prescriptions, the extended Press-Schechter theory. The unevolved subhalo mass functions at arbitrary mass scales become describable without introducing free parameters. The different host halo evolution histories are directly recast to their subhalo mass functions. As applications, we quantify the effects from (i) the Poisson fluctuation, (ii) the host mass scatter, and the (iii) different tidal evolution models on observables in the current Universe with this scheme. The Poisson fluctuation dominates in the number count of the mass ratio to the host of $\sim {\cal O}(10^{-2})$, where the intrinsic scatter is smaller by a factor of a few. The host-mass scatter around its mean does not affect the subhalo mass function. Different models of the tidal evolution predict a factor of ∼2 difference in numbers of subhalos with $\lesssim {\cal O}(10^{-5})$, while the dependence of the Poisson fluctuation on the tidal evolution models is subtle. The scheme provides a new tool for investigating the smallest-scale structures of our Universe which are to be observed in near future experiments.

Analytical models of dark matter subhalos for indirect dark matter searches

“…Simulations still provide invaluable information down to their resolution limit, especially on generic properties related to the almost scale-invariant character of hierarchical structure formation, most manifest in dark-matter-only simulations. In their range of validity, they are important to crosscheck predictions of analytical models [1,2]. They can also help better understand tidal processes and therefore develop methods based on physical principles (and not on extrapolations) to better account for or model these effects in arbitrary environments [3][4][5][6].…”

Searching for dark matter subhalos in the Fermi-LAT catalog with Bayesian neural networks

“…Our focus is on the population of dark substructures in the Milky Way, which can be modelled by studying the evolution of dark matter halos similar to our Galaxy through either fully JCAP07(2023)033 numerical cosmological simulations or simplified analytical models [3,[45][46][47][48]. While the signals from extragalactic substructures have also been studied [20,21,[49][50][51], we do not consider them in this analysis as we adopt a conservative approach.…”

Constraining the primordial curvature perturbation using dark matter substructure

“…In the calculation, we construct the evolution history of the host halo by applying the inverse function method to the above distribution function (see details for Ref. [58]). We start our calculation of the host halo evolution from z ¼ 0 and track its merger history up to z ¼ 300, taking 4000 points of a constant interval in the lnð1 þ zÞ space.…”