Gravitationally Consistent Halo Catalogs and Merger Trees for Precision Cosmology

TL;DR

This paper introduces a new algorithm for creating consistent halo catalogs and merger trees in cosmological simulations, improving accuracy and enabling uncertainty measurement in halo properties across time.

Contribution

The authors present a novel algorithm that ensures gravitational consistency of halo properties over time, enhancing catalog completeness, purity, and enabling direct uncertainty assessment.

Findings

Improved halo catalog completeness and purity.

Achieved 1-2% inconsistency in halo progenitors across simulations.

Validated the method on Bolshoi and Consuelo simulations.

Abstract

We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across timesteps. Our algorithm has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1-2% level across all halo masses. Our code is publicly available at http://code.google.com/p/consistent-trees . Our trees and catalogs are publicly available at http://hipacc.ucsc.edu/Bolshoi/ .