Stochastic Model of the Spin Distribution of Dark Matter Halos
Juhan Kim, Yun-Young Choi, Sungsoo S. Kim, and Jeong-Eun Lee

TL;DR
This paper models the distribution of dark matter halo spins using a stochastic approach, showing that a geometric Brownian motion explains the log-normal distribution and analyzing factors influencing angular momentum changes.
Contribution
It introduces a stochastic differential equation framework for halo spin evolution, linking random walks to observed spin distributions across different cosmic environments.
Findings
Spin changes follow a stochastic random walk pattern.
Generated spin distributions match simulations in group and cluster regions.
Log-normal distribution naturally arises from the stochastic model.
Abstract
We employ a stochastic approach to probing the origin of the log-normal distributions of halo spin in N-body simulations. After analyzing spin evolution in halo merging trees, it was found that a spin change can be characterized by a stochastic random walk of angular momentum. Also, spin distributions generated by random walks are fairly consistent with those directly obtained from N-body simulations. We derived a stochastic differential equation from a widely used spin definition and measured the probability distributions of the derived angular momentum change from a massive set of halo merging trees. The roles of major merging and accretion are also statistically analyzed in evolving spin distributions. Several factors (local environment, halo mass, merging mass ratio, and redshift) are found to influence the angular momentum change. The spin distributions generated in the mean-field…
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