pith. sign in

arxiv: 1610.01057 · v1 · pith:2ZGXJZFRnew · submitted 2016-10-04 · 🌌 astro-ph.GA · astro-ph.CO

The Mass Function of Unprocessed Dark Matter Halos and Merger Tree Branching Rates

classification 🌌 astro-ph.GA astro-ph.CO
keywords masshalomergern-bodyfunctionratescosmologicalfunctions
0
0 comments X
read the original abstract

A common approach in semi-analytic modeling of galaxy formation is to construct Monte Carlo realizations of merger histories of dark matter halos whose masses are sampled from a halo mass function. Both the mass function itself, and the merger rates used to construct merging histories are calibrated to N-body simulations. Typically, "backsplash" halos (those which were once subhalos within a larger halo, but which have since moved outside of the halo) are counted in both the halo mass function, and in the merger rates (or, equivalently, progenitor mass functions). This leads to a double-counting of mass in Monte Carlo merger histories which will bias results relative to N-body results. We measure halo mass functions and merger rates with this double-counting removed in a large, cosmological N-body simulation with cosmological parameters consistent with current constraints. Furthermore, we account for the inherently noisy nature of N-body halo mass estimates when fitting functions to N-body data, and show that ignoring these errors leads to a significant systematic bias given the precision statistics available from state-of-the-art N-body cosmological simulations.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A Unified Halo Mass Function Across Dark Matter Models from High-Resolution Multi-Scale Simulations

    astro-ph.CO 2026-06 unverdicted novelty 6.0

    A calibrated fitting function for the halo mass function that unifies predictions across CDM and non-CDM models over 10 orders of magnitude in mass with typical 12% precision after modeling systematics.