Investigating observational probes of galaxy evolution in observations and simulations

Abstract

In this thesis, we perform tests of galaxy evolution using a number of different observational
probes. In chapter 2, we implement a method of obtaining redshift distributions for photometric
samples of galaxies, known as clustering redshifts. We test this on real data from the
Baryon Oscillation Spectroscopic Survey (BOSS), and simulated data from semi-analytic models,
showing that assumptions about the bias evolution of the unknown sample can become
important for some samples of galaxies, particularly at faint magnitudes. We also find that
the choice of clustering scale makes a big difference to the noise in the recovered redshift
distribution. In chapter 3, we apply the clustering redshifts method to data from the Sloan
Digital Sky Survey (SDSS), recovering redshift distributions as a function of colour, allowing
us to compute mass and luminosity functions over large volumes. Little evolution is seen in
our recovered mass function between 0.2 < z < 0.8, implying the most massive galaxies form
most of their mass before z = 0.8. These mass functions are used to produce stellar mass completeness estimates for BOSS, giving a completeness of 80% above M_⋆ > 10^11.4 M_☉︎ between 0.2 < z < 0.7, with completeness falling significantly at higher redshifts and lower masses. In
chapter 4, we go on to investigate how well the formation history of a dark matter halo can
be inferred in simulations from the observable properties of a galaxy, finding that applying a
machine learning approach considering multiple properties performs significantly better than
using individual properties. We add errors to parameters, finding that a machine learning approach
still performs best, and finally use this approach to compute formation times for the
GAMA survey. We investigate how formation time changes with environment at fixed mass,
finding signs of assembly bias, with high mass halos in dense environments being younger
than those in under-dense regions, and the trend reversing at lower halo masses, with halos
in dense environments being older.

Date of Award	22 Jun 2022
Original language	English
Awarding Institution	University of St Andrews
Supervisor	Rita Tojeiro (Supervisor)