Related papers: Machine Learning and Cosmological Simulations II: …
We present ongoing hydrodynamic and MHD simulations of molecular cloud formation in spiral galaxies. The hydrodynamic results show the formation of molecular gas clouds where spiral shocks compress atomic gas to high densities. The spiral…
We perform an ensemble of $N$-body simulations with $2048^3$ particles for 101 flat $w$CDM cosmological models sampled based on a maximin-distance Sliced Latin Hypercube Design. By using the halo catalogs extracted at multiple redshifts in…
Recent focus on the importance of cold, unshocked gas accretion in galaxy formation -- not explicitly included in semi-analytic studies -- motivates the following detailed comparison between two inherently different modelling techniques:…
A fundamental prediction of the LambdaCDM cosmology is the hierarchical build-up of structure and therefore the successive merging of galaxies into more massive ones. As one can only observe galaxies at one specific time in cosmic history,…
Collisionless simulations of structure formation with significant local primordial non-Gaussianities at Mpc scales have shown that a non-Gaussian tail favouring underdensities, with a negative $f_{\rm NL}$ parameter, can significantly…
Machine learning (ML) provides a broad spectrum of tools and architectures that enable the transformation of data from simulations and experiments into useful and explainable science, thereby augmenting domain knowledge. Furthermore,…
Strong gravitational lensing offers a compelling test of the cold dark matter paradigm, as it allows for subhaloes with masses of $\sim10^{9}$ M$_\odot$ and below to be detected. We test commonly-used techniques for detecting subhaloes…
This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology. The pipeline includes…
We introduce the Virgo Consortium's EAGLE project, a suite of hydrodynamical simulations that follow the formation of galaxies and black holes in representative volumes. We discuss the limitations of such simulations in light of their…
Deep imaging programs, such as MATLAS which has just been completed at the CFHT, allows us to study with their diffuse light the outer stellar populations around large number of galaxies. We have carried out a systematic census of their…
There is increasing observational and theoretical evidence for a correlation between the metallicity and the mass of the stellar halo for galaxies with Milky Way-like stellar masses. Using the Illustris cosmological hydrodynamical…
We present the MUFASA suite of cosmological hydrodynamic simulations, which employs the GIZMO meshless finite mass (MFM) code including H2-based star formation, nine-element chemical evolution, two-phase kinetic outflows following scalings…
The formation of Hoag-type galaxies with central spheroidal galaxies and outer stellar rings has yet to be understood in astronomy. We consider that these unique objects were formed from the past interaction between elliptical galaxies and…
Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with non-trivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally…
We present the first study of evolution of galaxy groups in the Illustris simulation. We focus on dynamically relaxed and unrelaxed galaxy groups representing dynamically evolved and evolving galaxy systems, respectively. The evolutionary…
We study the properties of black holes and their host galaxies across cosmic time in the Illustris simulation. Illustris is a large scale cosmological hydrodynamical simulation which resolves a (106.5 Mpc)^3 volume with more than 12 billion…
The relationship between galaxies and haloes is central to the description of galaxy formation, and a fundamental step towards extracting precise cosmological information from galaxy maps. However, this connection involves several complex…
The simplest scheme for predicting real galaxy properties after performing a dark matter simulation is to rank order the real systems by stellar mass and the simulated systems by halo mass and then simply assume monotonicity - that the more…
We perform a comparison, object-by-object and statistically, between the Munich semi-analytical model, L-Galaxies, and the IllustrisTNG hydrodynamical simulations. By running L-Galaxies on the IllustrisTNG dark matter-only merger trees, we…
We apply and test a field-level emulator for non-linear cosmic structure formation in a volume matching next-generation surveys. Inferring the cosmological parameters and initial conditions from which the particular galaxy distribution of…