Universal Merger Histories of Dark-Matter Haloes
Eyal Neistein (MPA), Andrea V. Maccio' (MPIA), Avishai Dekel, (Hebrew Uni)

TL;DR
This paper introduces a universal fitting function for dark-matter halo merger histories across various cosmologies, enabling accurate transformations of merger trees and providing insights into their statistical properties.
Contribution
It presents a robust, universal fit for the conditional mass function of progenitor haloes and a method to transform merger histories across different cosmological models.
Findings
A universal fit for the conditional mass function applicable to multiple cosmologies.
A new technique for transforming merger histories between different models.
Confirmation that main-progenitor follows a log-normal distribution.
Abstract
We study merger histories of dark-matter haloes in a suite of N-body simulations that span different cosmological models. The simulated cases include the up-to-date WMAP5 cosmology and other test cases based on the Einstein-deSitter cosmology with different power spectra. We provide a robust fitting function for the conditional mass function (CMF) of progenitor haloes of a given halo. This fit is valid for the different cosmological models and for different halo masses and redshifts, and it is a significant improvement over earlier estimates. Based on this fit, we develop a simple and accurate technique for transforming the merger history of a given simulated halo into haloes of different mass, redshift and cosmology. Other statistics such as main-progenitor history and merger rates are accurately transformed as well. This method can serve as a useful tool for studying galaxy formation.…
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