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Genetically Modified Galaxies UNIVERSITY COLLEGE LONDON Faculty of Mathematical and Physical Sciences Department of Physics & Astronomy Genetically modified galaxies: performing controlled experiments in cosmological galaxy formation simulations Martin Pierre Rey Thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy of University College London Supervisors: Examiners: Dr. Andrew Pontzen Prof. George Efstathiou Dr. Amélie Saintonge Prof. Richard S. Ellis 6th of January, 2020 Martin Pierre Rey Genetically modied galaxies: performing controlled experiments in cosmological galaxy formation simula- tions Cosmology and Galaxy Formation, 6th of January, 2020 Examiners: Prof. George Efstathiou and Prof. Richard S. Ellis Supervisors: Dr. Andrew Pontzen and Dr. Amélie Saintonge UNIVERSITY COLLEGE LONDON Astrophysics Group Faculty of Mathematical and Physical Sciences Department of Physics & Astronomy Gower Street , WC1E 6BT London, UK Declaration I, Martin Pierre Rey, conrm that the work presented in this thesis is my own. Where information has been derived from other sources, I conrm that this has been indicated in the thesis. In particular, I would like to point out the following contributions: • Work presented in Chapter 2 is published in Rey and Pontzen (2018). • Work presented in Chapter 3 is published in Rey et al. (2019b). • Work presented in Chapter 4 has been submitted and is available online in Rey et al. (2019a). • Generating initial conditions for the results presented in Chapter 3, 4 and 5 has been performed using unpublished numerical methods, jointly developed by (alphabetically) Hiranya Peiris, Andrew Pontzen, Nina Roth, Stephen Stopyra and myself. This software will be released publicly in the near future (Stopyra et al. in prep). • Simulations presented in Chapter 4 and 5 are the result of a collaborative eort with (alphabetically) Oscar Agertz, Matthew Orkney, Andrew Pontzen, Justin Read and myself. A description of our model and numerical methods is available in Agertz et al. (2019) of which I am a co-author. • I also acknowledge the following people for contributing to this thesis through their hospitality during travels and useful discussions with myself: Lauren Anderson, Vasily Belokurov, Alyson Brooks, Aaron Ludlow, Andrey Kravtsov, Hiranya Peiris, Tjistke Starkenburg, Michael Tremmel, Anna Wright and the anonymous referee of Rey and Pontzen (2018). London, UK, 6th of January, 2020 Martin Pierre Rey Abstract This thesis develops and applies a novel approach to studying the formation of galaxies in our Universe. Galaxies grow through gravitational amplication of early-Universe overdensi- ties, within which gas reaches sucient densities to trigger star formation. A galaxy’s mass growth is therefore seeded randomly, originating from quantum inationary perturbations. Understanding how this intrinsic stochasticity in histories couples with strongly non-linear astrophysics is key to interpreting the observed diversity of the galaxy population. To provide new insights to this issue, we clarify and extend the “genetic modication” framework in Chapter 2. This approach generates alternative versions of a simulation’s initial conditions, each version with a carefully engineered change to the galaxy’s history. This in turn creates controlled experiments allowing us to construct a causal account of the galaxy’s response to modifying its merger history. We introduce a new class of variance modications aiming at improving control over several mergers. We then evolve these variance-modied initial conditions using the simulation code ramses, rst studying dark matter halo formation (Chapter 3). We causally recover the known correlation between halo formation time and concentration when modifying the merger histories of two haloes, and further establish how late major mergers determine concentrations at xed formation time. We then turn to the formation of ultra-faint dwarf galaxies with high-resolution hydrodynam- ical simulations. Scanning through histories, we demonstrate that earlier forming ultra-faints have higher stellar mass today and predict a new class of highly diuse ultra-faint galaxies which assemble through late mergers (Chapter 4). We nally use a larger suite of objects (Chapter 5) to show how ultra-faints growing suciently in dynamical mass after reionization can accrete gas and re-ignite star formation. We conclude that, by transforming cosmological histories into tuneable parameters, “genetically modied” experiments generate new insights on the complexity of dark matter halo and galaxy formation. 5 Impact Statement This thesis presents a combination of original analytical and computational works aimed at deepening our understanding of the formation of galaxies in our Universe. The benets of this corpus are primarily academic, developing and applying a new method to quantify the importance of mergers in shaping the diversity of galaxies. The theoretical underpinnings of the method (Chapter 2) were published in a leading astronomical journal and, together with the planned public release of our computational methods, will provide a reference for future use of the method throughout the astronomical community. Our applications presented in Chapter 3 and 4 have already achieved academic impact. They have been made publicly available through scientic publications, been cited by independent researchers across the world and led to new international collaborations for the author. Furthermore, Chapters 4 and 5 are likely to have long-lasting impact, predicting new classes of galaxies to be discovered in the coming decade by large-scale, hundred-million dollars, observational campaigns such as the Large Synoptic Survey Telescope. In addition to advancing our academic understanding of galaxies, this thesis adds to the broader context of determining our cosmic origins and the scientic quest to understand the composition of our Universe. Chapter 3, 4, 5 have indirect consequences for pinpointing the nature of dark matter, motivating the author to present some of their content in a public engagement campaign. Visualizations derived from Chapter 3 for example appeared in a public lecture attended by over 200 participants and discussed on local radio and newspapers. The computational nature of this thesis also reaches further than the academic world. Skills developed to achieve all chapters are applicable in numerous industrial and commercial con- texts; they were thus passed along by training fellow undergraduate and postgraduate students through optional teaching, mentoring and tutorials over the past three years. Moreover, Chap- ter 2 presents an algorithm to eciently solve constrained optimization problems over a large number of stochastic variables. The long-term impact of this algorithm is hard to quantify but such mathematical problems are routinely applied to inform decision making and cost minimiza- tion of commercial activities. Similarly, simulating hydrodynamics with massively-parallelised simulations over hundreds, if not thousands, of computers (Chapter 4 and 5) drives progress in 7 both high-performance computing and our understanding of uid dynamics. These advances can then be applied to industrial activities, for example optimizing the cost and environmental eciency of planes or predicting long-term weather and climate patterns. 8 Acknowledgements Many people have participated to the completion of this journey and it is a great pleasure to now acknowledge those to whom I am deeply indebted. First and foremost my two supervisors, Andrew Pontzen and Amélie Saintonge. Your dedication and support has guided me during the past three years, providing me with the best possible conditions to construct this manuscript. You have been incredible mentors, changing the way I reect about many problems (not just color schemes and fonts) and inspiring a taste for the academic world which might well be long-lasting. As obvious as it sounds, none of this would have been possible without you and I will never be able to thank you enough for it. I am also in debt to sta members over the world that guided and mentored my evolution through the academic world, oering me support, time, inspiration and hospitality when I needed it. It is a pleasure to thank in particular Oscar Agertz, Lauren Anderson, Alyson Brooks, Richard Ellis, Andreu Font-Ribera, Andrey Kravtsov, Hiranya Peiris, Justin Read, Tjitske Starkenburg and Michael Tremmel. An academic-style thesis will never reect how much fun it has been to interact with astronomers, in particular those at UCL. Group A has felt like a home for the past three years largely due to the number of friends I have made there. Thanks goes to Andreu for smuggling spanish ham into our squash sessions, Arthur for introducing me to the denition of right-wing politics, Boris for your always acidic stories, Catarina for sincerely trying to make the world a better place, Chris for our mutual taste of geekyness and puppies, Constance for understanding important needs in life such as Michelin starred food, Felix for your unquenchable thirst, Guido because one does not meet a third English-third Belgian-third Italian space traveler every day, Harry for introducing me to English must-sees like Road Wars, Isabella and Tom J. for hiding amazing wittiness under quietness, Keir for your incomparably dry sense of humour, Koki for your taste of radiatively transferred badminton, Krishna for your resilience in supporting Arsenal over the years, Lewis for teaching me the infamous Southampton-Liverpool
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