Exploring The Relation Between Galaxy Evolution and Galaxy Interaction
Creators: name: O'Ryan, David
Publisher: name: Lancaster University
Year: 2024

description: Hierarchical models and observations show that galaxy interaction and
 merging is of paramount importance to galaxy assembly and evolution.
 However, the relationship between these physical processes and the
 characteristics of the galaxies involved is unclear. In this thesis, we
 make direct constraints between the physical processes occurring in galaxy
 interaction - increased star formation, nuclear activity, and
 morphological disturbance - and the underlying parameters of galaxies -
 their interaction stage, stellar masses, kinematics, and orientation
 parameters. 
 
 
 To constrain these relations, we require large samples of interacting
 galaxies which are representative of the full underlying parameter space.
 A clear signature of interaction or merger activity is through the
 morphological distortion of a galactic system. We search for such
 signatures through the entire Hubble Space Telescope science archive with
 a Bayesian convolutional neural network. In total, we classify 92 million
 sources into interacting and non-interacting galaxies. We find 21,926
 disturbed and interacting galaxy systems; the largest interacting galaxy
 sample morphologically classified to date. 
 
 
 We use this new sample to explore the relationship between the dynamical
 timescale of interaction and galactic parameters. We match our new sample
 with the Cosmic Evolutionary Survey and find ancillary data for a volume
 limited sample of 3,378 interacting galaxies. We break this sample into
 four distinct stages aimed at capturing different parts of the dynamical
 timescale of interaction. We find evolution in the star formation rate
 with stage which cumulates in the complete disappearance of the red
 sequence at the merging stage. We find that the fraction of galaxies with
 an active galactic nuclei is constant with interaction stage, except at
 the point of coalescence where we find it increases from a measured value
 of 0.059 +/- 0.003 to an enhanced value of 0.071 +/- 0.005. By
 investigating the relationship between these fundamental processes and
 stage, we show that there is a direct relation between the interaction
 stage and the physical processes we observe. However, we require methods
 to more precisely probe the dynamical timescale of an interaction to make
 further constraints.
 
 
 Thus, we introduce a new algorithm which will be capable of exploring this
 relationship. We utilise a three-body numerical simulation with an
 Markov-Chain Monte Carlo (MCMC) algorithm to directly map the parameter
 space to tidal features. We constrain the underlying parameters of a
 sample of 51 synthetic images representing different observed interacting
 systems. We are able to recover the true parameters within a confidence
 interval of 86.4%. We apply this methodology to a subset of observational
 data, and explore the algorithm's potential as well as its
 limitations.
 
 
 The results of this thesis demonstrates the complex nature of the
 relationship between galaxy evolution and interaction, with larger samples
 and catalogues needed to constrain it. With the use of ESA Datalabs,
 building such samples is not just limited to interacting galaxies. It will
 allow the largest general galaxy morphology catalogues to date to be
 created. This, therefore, requires ever larger catalogues of ancillary
 data or the development of methods to efficiently create it. The
 introduction of a new algorithm to further investigate the relationship of
 interaction and its underlying parameters provides us a unique way to link
 interaction and evolution. The limitations of this algorithm are primarily
 due to the computational expense such a MCMC approach costs. We explore
 how this method can be developed, from bypassing the computational expense
 entirely with simulation based inference to new methods of optimisation
 with graphical processing units.