Related papers: The IllustrisTNG Simulations: Public Data Release
We use the TNG50 simulation of the IllustrisTNG project to study cold, dense clouds of gas in the circumgalactic media (CGM) of Milky Way-like galaxies. We find that their CGM is typically filled with of order one hundred (thousand)…
Almost two-thirds of disk galaxies in the local universe host bars, which serve as important drivers of secular evolutionary processes. While cosmological simulations are powerful tools to study the formation and evolution of galaxies, they…
We compute synthetic, rest-frame optical and ultraviolet (UV) emission-line properties of galaxy populations at redshifts from z$\approx$0 to z=8 in a full cosmological framework. We achieve this by coupling, in post-processing, the…
We use the IllustrisTNG simulations to explore the dynamic scaling relation between massive clusters and their central galaxies (BCGs). The Illustris TNG300-1 simulation we use includes 280 massive clusters with $M_{200} > 10^{14}$…
Modern redshift surveys are tasked with mapping out the galaxy distribution over enormous distance scales. Existing hydrodynamical simulations, however, do not reach the volumes needed to match upcoming surveys. We present results for the…
Indra is a suite of large-volume cosmological $N$-body simulations with the goal of providing excellent statistics of the large-scale features of the distribution of dark matter. Each of the 384 simulations is computed with the same…
We present the dynamical evolution of the dark matter's relaxation response to galaxies and their connection to the astrophysical properties as simulated in the IllustrisTNG suite of cosmological hydrodynamical simulations. Our results show…
Simulating the small-scale features and dynamics of the circumgalactic medium (CGM) is computationally challenging due to its large volume, low densities, multiphase structure, and chaotic environmental effects. Traditional mass-based…
We present GalSyn (Galaxy Synthesizer), a modular and flexible Python package for generating synthetic spectrophotometric observations from hydrodynamical galaxy simulations. GalSyn employs a particle-by-particle spectral modeling approach…
We use simulated cluster member galaxies from Illustris TNG300-1 to develop a technique for measuring the galaxy cluster mass accretion rate (MAR) that can be applied directly to observations. We analyze 1318 IllustrisTNG clusters of…
Galactic dynamical structures are fossil records of the assembly histories of galaxies. By analyzing the cosmological hydrodynamical simulation TNG50, we find that a dynamical structure that we call the "hot inner stellar halo," defined by…
It has been shown in previous publications that the TNG100 simulation quantitatively reproduces the observed reduction in each of the total atomic and total molecular hydrogen gas for galaxies within massive halos, i.e.~dense environments.…
We investigate a series of galaxy properties computed using the merger trees and environmental histories from dark matter only cosmological simulations, using a semi-recurrent neural network producing self-consistent predictions of galaxy…
We present a retuning of the IllustrisTNG baryonic physics model which can be used to run large-box realistic cosmological simulations with a lower resolution. This new model employs a lowered gas density threshold for star formation and…
We present Tangos, a Python framework and web interface for database-driven analysis of numerical structure formation simulations. To understand the role that such a tool can play, consider constructing a history for the absolute magnitude…
Active galactic nuclei (AGN) feedback plays a significant role in many aspects of galaxy formation and evolution and has become a key ingredient in cosmological simulations. However, the subgrid models of AGN feedback in cosmological…
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 grow and evolve in dark matter halos. Because dark matter is not visible, galaxies' halo masses ($\rm{M}_{\rm{halo}}$) must be inferred indirectly. We present a graph neural network (GNN) model for predicting $\rm{M}_{\rm{halo}}$…
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233…
Upcoming spectroscopic redshift surveys use emission line galaxies (ELGs) to trace the three-dimensional matter distributions with wider area coverage in the deeper Universe. Since the halos hosting ELGs are young and undergo infall towards…