Building models of the Universe with hydrodynamic simulations

Abstract

Hydrodynamic simulations have become irreplaceable in modern cosmology for exploring complex systems and making predictions to guide future observations. In this doctoral thesis, we address these challenges and explore the role of numerical simulations in advancing our understanding of galaxy formation. In Chapter 1, we begin our discussion by describing a philosophical framework for understanding the role of simulations in science. We argue that simulations can bridge the gap between empirical knowledge and fundamental, universal knowledge. The validation of simulation outcomes is crucial and stresses the importance of achieving a balance between trustworthiness and scepticism in the scientific community. Next, Chapter 2 introduces relevant cosmological concepts and outlines the processes leading to the formation of structures at early times and how numerical simulations can probe the growth of perturbations in the non-linear regime at late times. We discuss aspects of non-linear structure formation with hydrodynamics and baryonic physics, allowing for direct comparisons between synthetic and observational data. Chapter 3 provides technical details of numerical simulations, including the production pipeline of zoom-in simulations used to model individual objects in detail. We discuss the development of novel methods to mitigate known shortcomings. Then, we assessed the weak scaling performance of the SWIFT code in solving a purely hydrodynamic problem and found it to be one of the hydrodynamic codes with the highest parallel efficiency. In Chapter 4, we study the rotational kinetic Sunyaev-Zeldovich (rkSZ) effect for high-mass galaxy clusters from the MACSIS simulations. We find a maximum signal greater than 100 uK, approximately 30 times stronger than early predictions based on self-similar models, opening prospects for future observations. In Chapter 5, we address a tension between the distribution of entropy measured from observations and predicted by simulations of groups and clusters of galaxies. We find that most recent hydrodynamic simulations systematically over-predict the entropy profiles by up to one order of magnitude, leading to profiles that are shallower and higher than the power-law-like entropy profiles that have been observed. We discuss the dependence of the entropy distribution on different hydrodynamic and sub-grid parameters using variations of the EAGLE model, setting the directives for future work. Chapter 6 explores the evolution of global properties of groups and clusters of galaxies, together with the entropy profiles as a function of cosmic time. We identify four key phases in the evolution of these systems and report power-law-like entropy profiles at high redshift for both objects. However, at late times, an entropy plateau develops and alters the shape of the profile.

Date of Award	31 Dec 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Scott Kay (Supervisor) & Jens Chluba (Supervisor)