Excursion set peaks: a self-consistent model of dark halo abundances and clustering

TL;DR

This paper extends the excursion set peaks framework to better match dark halo abundances and clustering observed in simulations by incorporating physics-based modifications like a mass-dependent collapse threshold and scatter, achieving ~10% accuracy.

Contribution

It introduces a self-consistent model that includes a real-space TopHat filter, a mass-dependent critical density, and scatter, improving predictions of halo statistics compared to previous spherical collapse models.

Findings

Achieves ~10% accuracy in halo mass function predictions.

Excellent agreement with N-body halo bias measurements, especially at high masses.

Shows that incorporating physics-based modifications is essential for accurate modeling.

Abstract

We describe how to extend the excursion set peaks framework so that its predictions of dark halo abundances and clustering can be compared directly with simulations. These extensions include: a halo mass definition which uses the TopHat filter in real space; the mean dependence of the critical density for collapse delta_c on halo mass m; and the scatter around this mean value. All three of these are motivated by the physics of triaxial rather than spherical collapse. A comparison of the resulting mass function with N-body results shows that, if one uses delta_c(m) and its scatter as determined from simulations, then all three are necessary ingredients for obtaining ~10% accuracy. E.g., assuming a constant value of delta_c with no scatter, as motivated by the physics of spherical collapse, leads to many more massive halos than seen in simulations. The same model is also in excellent agreement with N-body results for the linear halo bias, especially at the high mass end where the traditional peak-background split argument applied to the mass function fit is known to underpredict the measured bias by ~10%. In the excursion set language, our model is about walks centered on special positions (peaks) in the initial conditions -- we discuss what it implies for the usual calculation in which all walks contribute to the statistics.