# Halo Exclusion Criteria Impacts Halo Statistics

## TL;DR

This paper shows that the arbitrary choice of percolation in halo-finding algorithms significantly affects halo statistics, impacting cosmological measurements like cluster abundance and weak lensing.

## Contribution

It demonstrates how different percolation choices in the ROCKSTAR halo finder alter halo catalogs and their statistical properties, highlighting the importance of this choice.

## Key findings

- Halo mass function varies by up to 10% due to percolation choice.
- Clustering bias differences reach comparable levels to current precision.
- Halo--matter correlation function differs by up to 40% on certain scales.

## Abstract

Every halo finding algorithm must make a critical yet relatively arbitrary choice: it must decide which structures are parent halos, and which structures are sub-halos of larger halos. We refer to this choice as ${\it percolation}$. We demonstrate that the choice of percolation impacts the statistical properties of the resulting halo catalog. Specifically, we modify the halo-finding algorithm ${\tt ROCKSTAR}$ to construct four different halo catalogs from the same simulation data, each with identical mass definitions, but different choice of percolation. The resulting halos exhibit significant differences in both halo abundance and clustering properties. Differences in the halo mass function reach $10\%$ for halos of mass $10^{13}\ h^{-1}\ {\rm M_{\odot}}$, larger than the few percent precision necessary for current cluster abundance experiments such as the Dark Energy Survey. Comparable differences are observed in the large-scale clustering bias, while differences in the halo--matter correlation function reach $40\%$ on translinear scales. These effects can bias weak-lensing estimates of cluster masses at a level comparable to the statistical precision of current state-of-the-art experiments.