Quantifying inhomogeneities in the HI distributions of simulated galaxies

Hind Al Noori,Andrea V Macciò,Aaron A Dutton,Keri L Dixon

doi:10.1088/1742-6596/1258/1/012023

Abstract

The NIHAO cosmological simulations form a collection of a hundred high-resolution galaxies. We used these simulations to test the impact of stellar feedback on the morphology of the HI distribution in galaxies. We ran a subsample of twenty of the galaxies with different parameterizations of stellar feedback, looking for differences in the HI spatial distribution and morphology. We found that different feedback models do leave a signature in HI, and can potentially be compared with current and future observations. These findings can help inform future modeling efforts in the parameterization of stellar feedback in cosmological simulations of galaxy formation and evolution.

Highlights

We are currently in the “golden age” of cosmology, with increasingly accurate measurements and constraints being placed on almost all cosmological parameters, painting a much richer conception of the Universe than was possible only a few decades ago
A very common and powerful tool used to study galaxy formation is via cosmological hydrodynamical simulations that allow us to examine the interplay of cosmological parameters such as dark matter with the physics of standard baryonic matter
Many cosmological simulations of galaxy formation have been performed in recent years, each inhabiting its own niche in the parameter space of possible physics

Summary

Introduction

We are currently in the “golden age” of cosmology, with increasingly accurate measurements and constraints being placed on almost all cosmological parameters, painting a much richer conception of the Universe than was possible only a few decades ago. In the form of supernova feedback and the winds of massive stars, was later discovered as a crucial ingredient in the physics of galaxy formation and has been shown to greatly alleviate the problem of the over-production of stars (Stinson et al, 2013).

Results

Conclusion