Related papers: Machine Learning and Cosmological Simulations II: …
We present a machine-learning framework, Machine Inferred Galaxy (MIG), to populate dark-matter haloes with galaxies in N-body simulations. MIG predicts stellar mass ($M_\ast$), star-formation rate (SFR), atomic and molecular gas masses…
We study how optical galaxy morphology depends on mass and star formation rate (SFR) in the Illustris Simulation. To do so, we measure automated galaxy structures in 10808 simulated galaxies at z=0 with stellar masses 10^9.7 < M_*/M_sun <…
The galaxy luminosity function and galaxy stellar mass function are fundamental statistics in the testing of galaxy formation models. Theoretical predictions based on cosmological simulations can deviate from observations, especially at the…
Cosmological hydrodynamical simulations, while the current state-of-the art methodology for generating theoretical predictions for the large scale structures of the Universe, are among the most expensive simulation tools, requiring upwards…
We present a cosmological hydrodynamical simulation of a 10^13 Msun galaxy group and its environment (out to 10 times the virial radius) carried out using the EAGLE model of galaxy formation. Exploiting a novel technique to increase the…
Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of…
We review theoretical approaches to the study of galaxy formation, with emphasis on the role of hydrodynamic simulations in modeling the high redshift galaxy population. We present new predictions for the abundance of star-forming galaxies…
LCDM is remarkably successful in predicting the cosmic microwave background and large-scale structure, and LCDM parameters have been determined with only mild tensions between different types of observations. Hydrodynamical simulations…
We present an image-based method for comparing the structural properties of galaxies produced in hydrodynamical simulations to real galaxies in the Sloan Digital Sky Survey. The key feature of our work is the introduction of extensive…
While cosmological dark matter-only simulations relying solely on gravitational effects are comparably fast to compute, baryonic properties in simulated galaxies require complex hydrodynamic simulations that are computationally costly to…
We develop a model to establish the interconnection between galaxies and their dark matter halos. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of halos/subhalos and the star…
Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of objects is also taken under consideration, it becomes very…
We use the Millennium Simulation, a 10 billion particle simulation of the growth of cosmic structure, to construct a new model of galaxy clustering. We adopt a methodology that falls midway between the traditional semi-analytic approach and…
We use the IllustrisTNG100 hydrodynamical simulation to study the dependence of the galaxy two-point correlation function on a broad range of secondary subhalo and galactic properties. We construct galaxy mock catalogues adopting a standard…
Galaxies co-evolve with their host dark matter halos. Models of the galaxy-halo connection, calibrated using cosmological hydrodynamic simulations, can be used to populate dark matter halo catalogs with galaxies. We present a new method for…
We use particle data from the Illustris simulation, combined with individual kinematic constraints on the mass of the Milky Way (MW) at specific distances from the Galactic center, to infer the radial distribution of the MW's dark matter…
We investigate how a property of a galaxy correlates most tightly with a property of its host dark matter halo, using state-of-the-art hydrodynamical simulations of galaxy formation EAGLE, Illustris, and IllustrisTNG. Unlike most of the…
We address the issue of numerical convergence in cosmological smoothed particle hydrodynamics simulations using a suite of runs drawn from the EAGLE project. Our simulations adopt subgrid models that produce realistic galaxy populations at…
Strong gravitational lensing provides a powerful tool to directly infer the dark matter (DM) subhalo mass function (SHMF) in lens galaxies. However, comparing observationally inferred SHMFs to theoretical predictions remains challenging, as…
Models of galaxy formation ultimately aim at reproducing the _observed_ properties of galaxies. We report on work in progress to predict luminosities, colours and morphologies of field objects of various masses through N-body + Smoothed…