The Bias and Mass Function of Dark Matter Halos in Non-Markovian Extension of the Excursion Set Theory

TL;DR

This paper extends the excursion set theory to include non-Markovian effects and stochastic barriers, providing a more accurate analytic model for predicting dark matter halo mass functions and bias, aligning better with N-body simulations.

Contribution

It introduces a non-Markovian extension of the excursion set theory with a stochastic barrier, enabling improved predictions of halo properties with only two key parameters.

Findings

Enhanced model matches N-body simulations more closely.

Analytic expressions for halo bias in non-Markovian context.

Model captures effects of filter shape and barrier stochasticity.

Abstract

The excursion set theory based on spherical or ellipsoidal gravitational collapse provides an elegant analytic framework for calculating the mass function and the large-scale bias of dark matter haloes. This theory assumes that the perturbed density field evolves stochastically with the smoothing scale and exhibits Markovian random walks in the presence of a density barrier. Here we derive an analytic expression for the halo bias in a new theoretical model that incorporates non-Markovian extension of the excursion set theory with a stochastic barrier. This model allows us to handle non-Markovian random walks and to calculate perturbativly these corrections to the standard Markovian predictions for the halo mass function and halo bias. Our model contains only two parameters: kappa, which parameterizes the degree of non-Markovianity and whose exact value depends on the shape of the filter function used to smooth the density field, and a, which parameterizes the degree of stochasticity of the barrier. Appropriate choices of kappa and a in our new model can lead to a closer match to both the halo mass function and halo bias in the latest N-body simulations than the standard excursion set theory.