Numerical Astrophysics: Galaxy Formation and Evolution

    General
    Description

    How galaxies formed and evolved through cosmic time is one of the key questions of modern astronomy and astrophysics. Cosmological time- and length-scales are so large that the evolution of individual galaxies cannot be directly observed. Only through numerical simulations can one follow the emergence of cosmic structures within the current cosmological paradigm.

    The main physical processes in galaxy formation and evolution are gravity, hydrodynamics, gas cooling, star formation, stellar evolution, supernova (SN) and black hole (BH) feedback. These are highly non-linear, thus difficult to describe with analytic models. Moreover, the presence of baryonic matter induces biases that collisionless (“dark matter”) simulations alone cannot reproduce (e.g. van Daalen et al. 2014, MNRAS, 440, 2997; Velliscig et al. 2014, MNRAS, 442, 2641). Semi-analytic models based on these simulations require ad hoc corrections to account for these biases. Hydrodynamic, cosmological simulations are therefore the preferred tool for conducting “controlled experiments” of galaxy formation and evolution.

    After three decades of advances in numerical simulations, theorists have only recently been able to reproduce simultaneously the observed properties of the present day galaxy population and the inter-galactic medium (e.g. EAGLE, Schaye et al. 2015, MNRAS, 446, 521; ILLUSTRIS, Vogelsberger et al., 2014, Nature, 509, 177). In particular, the luminosity and mass function of galaxies, the galaxy size- and metallicity-mass relations, and many other properties are now reproduced over a large range of galaxy stellar masses.

    The group of numerical astrophysics work on a variety of scientific topics related to the evolution of galaxies and the large-scale structure of the universe. The expertise ranges from the internal structure of dwarf and low surface brightness galaxies, the Milky Way and its satellite galaxies, the study of galaxies in groups and clusters, to large, cosmological simulations of the structure of the universe. The group collaborates with most of the IAC research groups working on extragalactic astrophysics and cosmology.

    Principal investigator
    Co Principal investigator

    EDGE/C-EAGLE With the completion of the main sample of simulations, the post-processing phase has been started. Dalla Vecchia developed an analysis program to compute luminosities of SSPs and magnitudes of galaxies of ~30 resimulated clusters. The code makes use of the stellar spectra library EMILES, developed at the IAC and recently extended to cover a larger wavelength range. EUCLID Within the EUCLID collaboration, a total of 300 cosmological, N-body simulations of a volume representative of the observed universe were performed. The same sample of initial conditions was evolved with different techniques by other members of the collaboration. The comparison of the different techniques will allow to assess their accuracy in the estimation of the covariance matrix, thus the errors in the measurements from large-scale structure surveys. GALAXY INTERACTIONS IN CLUSTERS For several decades, it has been known that stellar bars in disc galaxies can be triggered by interactions, or by internal processes such as dynamical instabilities. Martínez-Valpuesta et al. (2017) explore the differences between these two mechanisms using numerical simulations. They used two groups of simulations based on isolated galaxies, one group in which a bar develops naturally, and another group in which the bar could not develop in isolation. The rest of the simulations recreate 1:1 coplanar fly-by interactions computed with the impulse approximation. Compared with equivalent isolated galaxies, they find that bars affected or triggered by interactions: (i) remain in the slow regime for longer, (ii) are boxier in face-on views and (iii) they host kinematically hotter discs. Within this set of simulations, strong differences between retrograde or prograde fly-bys are not seen. They also show that slow interactions can trigger bar formation.

    Related publications

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    The role of active galactic nucleus feedback on the evolution of dwarf galaxies from cosmological simulations: Supermassive black holes suppress star formation in low-mass galaxies 2024A&A...690A.286A
    LIGHTS. Survey Overview and a Search for Low Surface Brightness Satellite Galaxies 2024AJ....168...69Z
    Exploring galaxy evolution time-scales in clusters: insights from the projected phase space 2024MNRAS.532..982S
    On the bright end of the UV luminosity functions of galaxies at z 0.6-1.2 2024MNRAS.531.2040S
    Characterising the intra-cluster light in The Three Hundred simulations 2024A&A...683A..59C
    On the dust properties of the UV galaxies in the redshift range z 0.6-1.2 2024MNRAS.528.1997S
    A high fidelity Milky Way simulation with Kraken, Gaia-Enceladus, and Sequoia analogues: clues to their accretion histories 2023MNRAS.526.1190G
    Constraining gas metal mixing strength in simulations using observations of the Milky Way's disc 2023MNRAS.525..279S
    Cosmic gas highways in C-EAGLE simulations 2023A&A...673A..62V
    On the anticorrelation between pericentric distance and inner dark matter density of Milky Way's dwarf spheroidal galaxies 2023MNRAS.522.3058C
    The Undiscovered Ultradiffuse Galaxies of the Local Group 2023ApJ...946L..37N
    A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies 2023MNRAS.519.4384E
    A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies
    Metallicity profiles of ultradiffuse galaxies in NIHAO simulations 2023MNRAS.519.1545C
    Linking the internal properties of infant globular clusters to their formation environments 2023MNRAS.518.4606P
    Mesh-free hydrodynamics in PKDGRAV3 for galaxy formation simulations 2023MNRAS.519..300A
    The luminosity of cluster galaxies in the Cluster-EAGLE simulations 2022MNRAS.515.2121N
    NIHAO-LG: the uniqueness of Local Group dwarf galaxies 2022MNRAS.512.6134A
    Observed versus simulated halo c-M<SUB>vir</SUB> relations 2022MNRAS.510L...4L
    FOREVER22: galaxy formation in protocluster regions 2022MNRAS.509.4037Y
    Formation of the first galaxies in the aftermath of the first supernovae 2021MNRAS.508.3226A
    A Shallow Dark Matter Halo in Ultra-diffuse Galaxy AGC 242019: Are UDGs Structurally Similar to Low-surface-brightness Galaxies? 2021ApJ...919L...1B
    Pericentric passage-driven star formation in satellite galaxies and their hosts: CLUES from local group simulations 2021MNRAS.506..531D
    Origin of stellar prolate rotation in a cosmologically simulated faint dwarf galaxy 2021MNRAS.505L.100C
    History of the gas fuelling star formation in EAGLE galaxies 2021MNRAS.505.4655S
    Higher order Hamiltonian Monte Carlo sampling for cosmological large-scale structure analysis 2021MNRAS.502.3976H
    Evaluating hydrodynamical simulations with green valley galaxies 2021MNRAS.502.3685A
    Self-interacting dark matter and the delay of supermassive black hole growth 2021MNRAS.500.2177C
    Stellar splashback: the edge of the intracluster light 2021MNRAS.500.4181D
    The discovery of the most UV-Ly α luminous star-forming galaxy: a young, dust- and metal-poor starburst with QSO-like luminosities 2020MNRAS.499L.105M
    The First Billion Years project: Finding infant globular clusters at z = 6 2020A&A...641A.132P
    NIHAO XXIV: rotation- or pressure-supported systems? Simulated Ultra Diffuse Galaxies show a broad distribution in their stellar kinematics 2020MNRAS.497.4282C
    Constraining the inner density slope of massive galaxy clusters 2020MNRAS.496.4717H
    Explaining the chemical trajectories of accreted and in-situ halo stars of the Milky Way 2020MNRAS.495.2645B
    Kinematic analysis of eagle simulations: evolution of λ<SUB>Re</SUB> and its connection with mergers and gas accretion 2020MNRAS.494.5652W
    The mass of our Galaxy from satellite proper motions in the Gaia era 2020MNRAS.494.5178F
    Sub one per cent mass fractions of young stars in red massive galaxies 2020NatAs...4..252S
    The intracluster light as a tracer of the total matter density distribution: a view from simulations 2020MNRAS.494.1859A
    Deep spectroscopy in nearby galaxy clusters - V. The Perseus cluster 2020MNRAS.494.1681A

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