Achieving Convergence in Galaxy Formation Models by Augmenting N-body Merger Trees

TL;DR

This paper introduces a method to improve the resolution of N-body merger trees in galaxy formation models by grafting higher-resolution Monte Carlo branches, leading to more accurate and converged galaxy property predictions.

Contribution

The paper presents a novel augmentation technique for N-body merger trees using Monte Carlo branches to achieve convergence in galaxy formation simulations.

Findings

Augmentation method improves convergence of galaxy properties.

Grafted trees produce consistent and higher-resolution merger histories.

Enhanced models better match observed galaxy characteristics.

Abstract

Accurate modeling of galaxy formation in a hierarchical, cold dark matter universe requires the use of sufficiently high-resolution merger trees to obtain convergence in the predicted properties of galaxies. When semi-analytic galaxy formation models are applied to cosmological N-body simulation merger trees, it is often the case that those trees have insufficient resolution to give converged galaxy properties. We demonstrate a method to augment the resolution of N-body merger trees by grafting in branches of Monte Carlo merger trees with higher resolution, but which are consistent with the pre-existing branches in the N-body tree. We show that this approach leads to converged galaxy properties.