Theory at a Crossroads: An In-depth Look at Simulations of Galaxy Interactions A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MANOA¯ IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN ASTRONOMY August 2019 By Kelly Anne Blumenthal Dissertation Committee: J. Barnes, Chairperson L. Hernquist J. Moreno R. Kudritzki B. Tully M. Connelley J. Maricic © Copyright 2019 by Kelly Anne Blumenthal All Rights Reserved ii This dissertation is dedicated to the amazing administrative staff at the Institute for Astronomy: Amy Miyashiro, Karen Toyama, Lauren Toyama, Faye Uyehara, Susan Lemn, Diane Tokumura, and Diane Hockenberry. Thank you for treating us all so well. iii Acknowledgements I would like to thank several people who, over the course of this graduate thesis, have consistently shown me warmth and kindness. First and foremost: my parents, who fostered my love of astronomy, and never doubted that I would reach this point in my career. Larissa Nofi, my partner in crime, has been my perennial cheerleader – thank you for never giving up on me, and for bringing out the best in me. Thank you to David Corbino for always being on my side, and in my ear. To Mary Beth Laychack and Doug Simons: I would not be the person I am now if not for your support. Thank you for trusting me and giving me the space to grow. To my east coast advisor, Lars Hernquist, thank you for hosting me at Harvard and making time for me. To my dear friend, advisor, and colleague Jorge Moreno: you are truly inspirational. Thank you for being unabashedly yourself in every context, for standing up for what you believe is right, and for investing so much into my success. Working with you has reminded me why I wanted to do this in the first place. Last, but certainly not least, thank you to my advisor, Joshua Barnes. We have been through quite a bit over the last five years, and you have been unwaveringly kind to me at every step of the way. Thank you for teaching me all that you have, thank you for nurturing my curiosity, and thank you for trusting me as much as you do. It is profoundly reassuring to know that people like you are still in the field. I would also like to recognize the National Science Foundation Graduate Research Fellowship (Grant No. DGE-1329626); without this financial and professional support, I would not have been able to carry out this thesis. Though this thesis does not use any data from Maunakea Observatories, I feel it is important to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. As astronomers, we are incredibly fortunate to have the opportunity to conduct observations from this mountain. Without the mauna, there would be no Institute for Astronomy, and no graduate thesis today. I owe the indigenous Hawaiian community a great debt for sharing their skies and knowledge with the world. iv Abstract While cosmological simulations capture a wealth of information regarding how galaxies evolve in their large-scale environment, idealized simulations can achieve high spatial, temporal, and mass resolution. The subgrid physics models which lead to the successes of cosmological simulations are developed and perfected using idealized simulations. Idealized simulations remain valuable but need to be updated according to the findings of cosmological simulations and modern observations. The primary concern of this thesis is to explore the limitations of idealized simulations and provide suggestions to improve the methodology. Observations have shown that the gas discs of spiral galaxies are always the same size or larger than stellar discs. Despite this, most idealized simulations of galaxy interactions employ equal-sized discs. I present a series of experiments which investigate the consequences of this assumption: the magnitude and efficiency of inflow is affected by a confluence of structural and orbital parameters. Idealized simulations are informed by observational catalogues. These typically use the projected separation and tidal features to identify merging systems, both of which are subject to biases. To assess these biases, I create a sample of interacting pairs from IllustrisTNG. I generate mock observations of the simulated pairs and use both observational techniques and the full cosmological data to determine that ∼45% of these pairs are visually identifiable as interacting. In this work, I show that local merger samples constructed from stellar features are likely to be incomplete and biased toward certain environments. I then use the merger sample to perform a series of tests that assess the validity of the Keplerian (ideal) approximation. Many aspects are consistent with cosmological simulation, however accretion onto the halo provides a non-negligible amount of mass and momentum which has significant effects on galaxies’ trajectories. I provide distributions of infall conditions as a primer for future idealized simulations, and additionally present a case study that tests the proposed methodology. Under certain circumstances, the idealized prescription is able to predict orbital parameters such as the time of first pericenter. v Table of Contents Acknowledgements . iv Abstract . .v List of Tables . ix List of Figures . .x Chapter 1: Physics Introduction . .1 1.1 Galactic Dynamics . .4 1.1.1 Collisionless Systems . .5 1.1.2 Gaseous Systems . .5 1.1.3 Gravity . .6 1.2 The Interstellar Medium . .8 1.2.1 Atomic and Molecular Hydrogen . .8 1.2.2 Heating and Cooling . .8 1.3 Stellar Physics . .9 1.3.1 Star Formation . .9 1.3.2 Stellar Evolution . 10 1.4 Galactic-Scale Physics . 12 1.4.1 Magnetic Fields . 12 1.4.2 Active Galactic Nuclei . 12 Chapter 2: Introduction to Computational Methods . 25 2.1 The N-Body Method . 25 2.1.1 Hierarchical Force Calculation (Barnes-Hut Tree) . 25 2.1.2 Particle-Mesh Algorithm . 26 vi 2.2 Hydrodynamic Methods . 27 2.2.1 Smoothed-Particle Hydrodynamics . 27 2.2.2 Moving-Mesh Hydrodynamics (AREPO) . 28 2.3 Zeno . 28 2.4 IllustrisTNG . 29 2.4.1 Coordinate systems . 32 2.4.2 Simulation Algorithms . 32 2.4.3 Post-Processing Methods . 36 2.5 Dissertation Outline . 39 Chapter 3: Inflow Mechanisms in Idealized Simulations of Galaxy Collisions . 46 3.1 Preamble . 46 3.2 Abstract . 46 3.3 Introduction . 47 3.4 Methods . 50 3.4.1 Galaxy Models . 51 3.4.2 Encounter Models . 55 3.5 Analysis . 56 3.5.1 Inflow . 57 3.5.2 Inflow Mechanisms . 60 3.6 Discussion . 68 3.6.1 Previous Descriptions of Clumps . 68 3.6.2 Resolution Considerations . 69 3.6.3 Missing Subgrid Physics . 70 3.7 Conclusions . 71 Chapter 4: Galaxy interactions in IllustrisTNG-100, I: The power and limitations of visual identification 78 4.1 Preamble . 78 4.2 Abstract . 78 4.3 Introduction . 79 4.4 Methods . 81 4.4.1 IllustrisTNG . 81 vii 4.4.2 Galaxy Pair Samples . 84 4.5 Results and Discussion . 89 4.5.1 The VIP and nonVIP Samples . 89 4.5.2 Galaxy pair dynamics . 90 4.5.3 Star Formation Main Sequence . 93 4.5.4 Gas Content . 98 4.5.5 Tidal features . 99 4.5.6 Environment . 100 4.6 Conclusions . 105 Chapter 5: Galaxy interactions in IllustrisTNG, II: Orbit characterization and lessons for idealized simulations . 124 5.1 Abstract . 124 5.2 Introduction . 124 5.3 Methods . 126 5.3.1 IllustrisTNG . 126 5.3.2 Overview of Chapter 4 . ..