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It is generally agreed that the galaxies in our Universe form and evolve within haloes of dark matter. The formation and evolution of the dark matter density field is believed to leave a profound imprint on the luminous matter that traces galaxy properties. Although the precise way dark matter haloes shape galaxies is currently hotly debated, the structural, morphological and dynamical evolution of galaxies are considered important probes of the interplay between galaxies and their dark matter haloes. The aim of this thesis is to study galaxy evolution through the lens of galaxy structure and morphology by taking a holistic approach which encompasses data-driven and existing physical models. In particular, I devise semi-empirical models for galaxy structure, which have been introduced only recently, and I also include novel deep learning methods in the modelling stack. Firstly, I will use statistical modelling to derive empirical relationships between galaxies and their dark matter haloes, setting constraints on the physical processes arising from dark matter that set galaxy structure and dynamics. Secondly, I take state-of-the-art hydrodynamical simulations of galaxy formation that meet these constraints, and I evaluate the small-scale structural details of simulated galaxies against real observations. By treating this problem as an unsupervised Out of Distribution detection task, I show that simulations are improving over the years, but they are yet to agree perfectly with observational data. Thirdly, I further test the semi-empirical models above on the fast structural growth of Massive Galaxies and on the weak dependence of their size on the large-scale environment, and provide predictive trends for future observations. Finally, in the spirit of transferring knowledge from Astronomy and Astrophysics to other fields, I apply similar modelling techniques to Medicine to assess the effectiveness of current management strategies for hypertension.

The formation of Ultra Massive Galaxies (UMGs, Mstar>10^11.2 Msun) is debated. The physical sizes of UMGs are an important probe of possible formation scenarios for these galaxies. In this theoretical work we investigate the evolution of the size distributions of UMGs, which has been little explored so far at high redshift, but that will become available with the wide coverage area offered by the Roman Telescope. To do so, we adopt a semi-empirical approach based on the stellar mass-halo mass (SMHM) relation and the galaxy size-halo size (GSHS) relation. The GSHS is sufficient to broadly reproduce the mean size evolution of UMGs out to z~3. We also show that the predicted evolution of the number density of compact UMGs implied by a tight GSHS (supported by low z data) agrees with formation scenarios where the late evolution of UMGs is dominated by the growth of individual galaxies, while at high redshift most UMGs build up in a compact phase, which supports a progenitor bias scenario at early epochs. The GSHS relation can make explicit predictions on environmental trends of galaxy sizes as well as on the number density of compact relics which survived as satellites. The predictions significantly depend on the SMHM relation - possibly a consequence of the different contributions from in-situ and ex-situ processes implied by different physical models. Thus, the large sample of UMGs observed by Roman Telescope will help constrain the galaxy-halo connection and galaxy evolution.

Accurately reproducing the morphology of galaxies in our Universe is a crucial test for hydrodynamical cosmological simulations of galaxy evolution. We assess the extent to which the fine details of the stellar galaxy morphology are reproduced in simulations using a novel deep learning approach. Our unsupervised methodology provides a metric that is a robust measure of the relationship between the galaxy morphological details and its overall structure, which goes well beyond current parametric and non-parametric approaches. We test fully realistic r-band mock observations of galaxies from the Illustris simulation and the improved IllustrisTNG model against SDSS observations. We can quantitatively identify the improvements of IllustrisTNG, particularly in the high-resolution TNG50 run, over the original Illustris. However, we find that the fine details of galaxy structure are still different between observed and simulated galaxies. This difference is driven by small, spheroidal, and quenched galaxies which are globally less accurate regardless of resolution and which have experienced little improvement between the simulations explored. We speculate that this disagreement may stem from a still too coarse numerical resolution, which struggles to properly capture the inner, dense regions of quenched spheroidal galaxies. I will also present efforts being made to extend this strategy to HST data, and will put these in the perspective of the coverage area of the Roman telescope.&nbsp

Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed across galaxy scaling relations are important probes of our knowledge of galaxy formation physics. Here we propose an unsupervised deep learning approach to perform a stringent test of the fine morphological structure of galaxies coming from the Illustris and IllustrisTNG (TNG100 and TNG50) simulations against observations from a subsample of the Sloan Digital Sky Survey. Our framework is based on PixelCNN, an autoregressive model for image generation with an explicit likelihood. We adopt a strategy that combines the output of two PixelCNN networks in a metric that isolates the fine morphological details of galaxies from the sky background. We are able to \emph{quantitatively} identify the improvements of IllustrisTNG, particularly in the high-resolution TNG50 run, over the original Illustris. However, we find that the fine details of galaxy structure are still different between observed and simulated galaxies. This difference is driven by small, more spheroidal, and quenched galaxies which are globally less accurate regardless of resolution and which have experienced little improvement between the three simulations explored. We speculate that this disagreement, that is less severe for quenched disky galaxies, may stem from a still too coarse numerical resolution, which struggles to properly capture the inner, dense regions of quenched spheroidal galaxies., Accepted for publication in MNRAS. Comments welcome

A supermassive black hole has been found at the centre of nearly every galaxy observed with sufficient sensitivity. The masses of these black holes are observed to increase with either the total mass or the mean (random) velocity of the stars in their host galaxies. The origin of these correlations remains elusive. Observational systematics and biases severely limit our knowledge of the local demography of supermassive black holes thus preventing accurate model comparisons and progress in this field. Here we show that the large-scale spatial distribution of local active galactic nuclei (AGN), believed to be accreting supermassive black holes, can constrain the shape and normalization of the black hole-stellar mass relation thus bypassing resolution-related observational biases. In turn, our results can set more stringent constraints on the so-called "radiative efficiency", a fundamental parameter describing the inner physics of supermassive black holes that is closely linked to their spin, geometry, and ability to release energy. The mean value of the radiative efficiency can be estimated by comparing the average total luminous output of AGN with the relic mass density locked up in quiescent supermassive black holes at galaxy centres today. For currently accepted values of the AGN obscured fractions and bolometric corrections, our newest estimates of the local supermassive black hole mass density favour mean radiative efficiencies of ~10-20\%, suggesting that the vast majority of supermassive black holes are spinning moderately to rapidly. With large-scale AGN surveys coming online, our novel methodology will enable even tighter constraints on the fundamental parameters that regulate the growth of supermassive black holes., Comment: 31 pages, 7 Figures. Accepted

The masses of supermassive black holes at the centres of local galaxies appear to be tightly correlated with the mass and velocity dispersions of their galactic hosts. However, the local Mbh–Mstar relation inferred from dynamically measured inactive black holes is up to an order-of-magnitude higher than some estimates from active black holes, and recent work suggests that this discrepancy arises from selection bias on the sample of dynamical black hole mass measurements. In this work, we combine X-ray measurements of the mean black hole accretion luminosity as a function of stellar mass and redshift with empirical models of galaxy stellar mass growth, integrating over time to predict the evolving Mbh–Mstar relation. The implied relation is nearly independent of redshift, indicating that stellar and black hole masses grow, on average, at similar rates. Matching the de-biased local Mbh–Mstar relation requires a mean radiative efficiency ε ≳ 0.15, in line with theoretical expectations for accretion on to spinning black holes. However, matching the ‘raw’ observed relation for inactive black holes requires ε ∼ 0.02, far below theoretical expectations. This result provides independent evidence for selection bias in dynamically estimated black hole masses, a conclusion that is robust to uncertainties in bolometric corrections, obscured active black hole fractions, and kinetic accretion efficiency. For our fiducial assumptions, they favour moderate-to-rapid spins of typical supermassive black holes, to achieve ε ∼ 0.12–0.20. Our approach has similarities to the classic Soltan analysis, but by using galaxy-based data instead of integrated quantities we are able to focus on regimes where observational uncertainties are minimized., FS acknowledges partial support from a Leverhulme Trust Research Fellowship. RC acknowledges financial support from CONICYT Doctorado Nacional N° 21161487 and CONICYT PIA ACT172033. DMA thanks the Science and Technology Facilities Council (STFC) for support from grant no. ST/L00075X/1. ID is supported by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 788679. MM acknowledges support from the Beatriu de Pinos fellowship (2017-BP-00114).

We carry out a systematic investigation of the total mass density profile of massive (Mstar~3e11 Msun) early-type galaxies and its dependence on redshift, specifically in the range 0, Comment: 14 pages, 8 figures. MNRAS, accepted. Main result of the paper in Figure 2