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Adrien Christian René THOB

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Adrien Christian René THOB THE RELATIONSHIP BETWEEN THE MORPHOLOGY AND KINEMATICS OF GALAXIES AND ITS DEPENDENCE ON DARK MATTER HALO STRUCTURE IN SIMULATED GALAXIES Adrien Christian René THOB A thesis submitted in partial fulfilment of the requirements of Liverpool John Moores University for the degree of Doctor of Philosophy. 26 April 2019 To my grand-parents, René Roumeaux, Christian Thob, Yvette Roumeaux (née Bajaud) and Anne-Marie Thob (née Léglise). ii Abstract Galaxies are among nature’s most majestic and diverse structures. They can play host to as few as several thousands of stars, or as many as hundreds of billions. They exhibit a broad range of shapes, sizes, colours, and they can inhabit vastly differing cosmic environments. The physics of galaxy formation is highly non-linear and in- volves a variety of physical mechanisms, precluding the development of entirely an- alytic descriptions, thus requiring that theoretical ideas concerning the origin of this diversity are tested via the confrontation of numerical models (or “simulations”) with observational measurements. The EAGLE project (which stands for Evolution and Assembly of GaLaxies and their Environments) is a state-of-the-art suite of such cos- mological hydrodynamical simulations of the Universe. EAGLE is unique in that the ill-understood efficiencies of feedback mechanisms implemented in the model were calibrated to ensure that the observed stellar masses and sizes of present-day galaxies were reproduced. We investigate the connection between the morphology and internal 9:5 kinematics of the stellar component of central galaxies with mass M? > 10 M in the EAGLE simulations. We compare several kinematic diagnostics commonly used to describe simulated galaxies, and find good consistency between them. We model the structure of galaxies as ellipsoids and quantify their morphology via the ratios of their principal axes. We show that the differentiation of blue star-forming and red quiescent galaxies using morphological diagnostics can be achieved with similar efficacy to the use of kinematical diagnostics, but only if one is able to measure both the flattening and the triaxiality of the galaxy. Flattened oblate galaxies exhibit greater rotational support than their spheroidal counterparts, but there is significant scatter in the relationship between morphological and kinematical diagnostics, such that kinematically-similar iii galaxies can exhibit a broad range of morphologies. The scatter in the relationship between the flattening and the ratio of the rotation and dispersion velocities (v/σ) cor- relates strongly with the anisotropy of the stellar velocity dispersion: at fixed v/σ, flatter galaxies exhibit greater dispersion in the plane defined by the intermediate and major axes than along the minor axis, indicating that the morphology of simulated galaxies is influenced significantly by the structure of their velocity dispersion. The simulations reveal that this anisotropy correlates with the intrinsic morphology of the galaxy’s inner dark matter halo, i.e. the halo’s morphology that emerges in the absence of dissipative baryonic physics. This implies the existence of a causal relationship be- tween the morphologies of galaxies and that of their host dark matter haloes. Using these tools, we also investigate the morphology and kinematics of central galaxies with 9:5 mass M? > 10 M and their globular cluster (GC) populations in the EAGLE spin- off project E-MOSAICS that incorporates the MOSAICS model of stellar cluster for- mation and evolution. We find that metal-poor and metal-rich GC populations (split by a threshold at [Fe=H] = −1) exhibit differing characteristic morpho-kinematic prop- erties. The former are significantly more elliptical and dispersion-supported than the latter. In detail, the relations connecting the kinematic properties of the populations with those of their host galaxy exhibit good agreement with available observations, with the velocity dispersions of both metal-poor and metal-rich GC populations corre- lating positively with that of the host galaxy. The rotational velocity of the metal-rich globular cluster population also correlates positively with that of the host galaxy. The relationship between the morpho-kinematics of the metal-rich globular clusters and the host galaxy’s field stars exhibits a scatter that is sensitive to the relative ages of the two populations: for fixed globular cluster kinematics, the field star population is more disky/rotation-supported if they are younger. We confirm that the connection between the morpho-kinematics of galaxies and their velocity dispersion anisotropy revealed in EAGLE is also exhibit in the higher-resolution E-MOSAICS simulation. However, the same behaviour is not seen in the metal-rich globular clusters, which we speculate is a consequence of them not representing a self-gravitating system. ADRIEN CHRISTIAN RENÉ THOB JULY 9, 2019 iv Contents Abstract iii Contents v Figures . .x Declaration xiii Credits . xiv Publications . xv Acknowledgements . xvi 1 General introduction 1 1.1 A consensus around the ΛCDM paradigm . .4 1.1.1 The cold dark matter structure formation . .5 1.1.2 Freezing quantum fluctuations through cosmic inflation . .6 1.1.3 The accelerating expansion via dark energy . .7 1.2 Galaxy formation and diversity . .8 1.2.1 Hierarchical formation . .9 1.2.2 Star formation and colour bimodality . 11 v 1.2.3 Galaxy feedback processes . 13 1.3 Morpho-kinematics in galaxies . 15 1.3.1 Late and early type galaxies . 16 1.3.2 Diversity in kinematics . 17 1.3.3 Morphologies vs. kinematics: simulations as a laboratory . 17 2 Simulating the Universe: computational cosmology 19 2.1 Introduction . 19 2.2 Cosmological hydrodynamics: generic structure . 21 2.2.1 Gravity solver . 22 2.2.2 Inclusion of gas dynamics . 24 2.2.3 Subgrid physics . 26 2.3 Simulations . 29 2.3.1 The EAGLE model . 29 2.3.2 The E-MOSAICS simulations . 32 2.3.3 Identifying and characterizing galaxies . 34 2.4 Summary . 35 3 Morphologies, kinematics and galaxy colours 37 3.1 Introduction . 37 3.2 Galactic dynamics modelling . 39 3.3 Measuring shapes in simulations . 42 3.3.1 Quadrupole moments of the mass distribution . 43 vi 3.3.2 Diversity of ellipsoidal shapes . 45 3.4 Measuring dynamics in simulations . 47 3.4.1 Characterising galaxy kinematics . 48 3.4.2 A brief comparison of kinematical diagnostics . 52 3.5 Correspondence with the colour-stellar mass relation . 55 3.6 Summary and discussions . 58 4 Stellar morpho-kinematics and halo structure 60 4.1 Introduction . 60 4.2 Relationship between morphology and kinematics . 61 4.2.1 Numerical convergence test . 63 4.2.2 Prolate kinematically misaligned galaxies . 65 4.2.3 Oblate rotators and spheroids . 66 4.3 The origin of the velocity anisotropy . 69 4.3.1 Dark matter and stellar structures . 70 4.3.2 Dispersion anisotropy and dark matter . 73 4.4 Summary and discussions . 74 5 Morpho-kinematics of globular cluster systems and their host galaxy 77 5.1 Introduction . 77 5.2 Numerical methods . 79 5.2.1 Identifying galaxies and their globular cluster populations . 80 5.2.2 Characterising morphology . 81 vii 5.2.3 Characterizing kinematics . 82 5.3 Results . 83 5.3.1 Globular cluster demographics . 83 5.3.2 Correspondence of GC and host galaxy properties . 85 5.3.3 Morpho-kinematic relationship . 98 5.4 Summary and discussions . 100 6 Conclusions and future works 104 6.1 Summary . 105 6.2 Future directions . 109 6.2.1 Expanding our results . 109 6.2.2 Exploiting our tools . 111 A Rendering cosmological simulations 112 A.1 Software development . 113 A.1.1 PY-SPHVIEWER renderer . 113 A.1.2 Main scheme & and recent improvements . 115 A.2 Extrinsic applications . 117 A.2.1 Oppenheimer et al. (2016) Press release . 117 A.2.2 Fiske planetarium demonstration . 118 A.3 Future implementation ideas . 120 A.3.1 Refining orientation interpolation . 120 A.3.2 Higher framerate resolution . 121 viii A.3.3 Additional projection schemes . 122 Bibliography 123 ix Figures 1.1 Difference between halo and stellar mass function (adapted from on- line material by M. Whittle) . 10 1.2 Galaxy colour-stellar mass diagram (Schawinski et al., 2014) . 12 1.3 Stellar-to-halo mass ratio of central galaxies (Wechsler and Tinker, 2018; Behroozi et al., 2018) . 13 1.4 Hubble (1926b) tuning fork classification of galaxies (as adapted from Wikimedia Commons) . 15 2.1 Example of multi-component composition of a cosmological hydrody- namics simulation (adapted from a rendering made for the Lynx X-Ray Observatory - Section A.2.2) . 28 3.1 Analytical relation between the rotation-to-dispersion ratio, vrot/σ0, the flattening, , and the dispersion anisotropy, δ, from the tensor virial theorem (eq. 3.5) . 42 3.2 Two-dimensional distribution of central galaxies in the parameter space defined by the triaxiality, T , and flattening, , shape parameters (see eq. 3.7) . 46 3.3 Relationship between the rotation-to-dispersion ratio vrot/σ0 and other kinematic diagnostics commonly used to characterise simulated galaxies 53 ? ? 3.4 Present-day (u − r ) − M? relation defined by our sample of central galaxies with their morpho-kinematics . 56 4.1 Relationship between vrot/σ0 and for central galaxies with stellar 9:5 masses above 10 M ......................... 62 4.2 Convergence test for the relationship between vrot/σ0 and ...... 64 x 4.3 Relationship between the distribution shown in figure 3.2 and the rota- ~ k~a≡1 tional orientation parameter bLek~c≡0 .................. 66 4.4 The morpho-kinematics relationship vrot/σ0 - as a function of the dispersion anisotropy δ in spheroidals and oblate rotators . 67 4.5 The morpho-kinematics relationship vrot/σ0 - as a function of both Ref DMO the inner dark matter halo flattening dm and intrinsic flattening dm in spheroidals and oblate rotators . 71 4.6 Median relations of the flattening deviation at fixed vrot/σ0 and of the dispersion anisotropy δ with both the inner dark matter halo flattening Ref DMO dm and intrinsic flattening dm ...................
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