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The star-formation activity of IllustrisTNG galaxies: main sequence, UVJ diagram, quenched fractions, and systematics
Martina Donnari, Annalisa Pillepich, Dylan Nelson +6
We select galaxies from the IllustrisTNG hydrodynamical simulations ( at ) and characterize the shapes and evolutions of their UVJ and star-format…
The IllustrisTNG Simulations: Public Data Release
Dylan Nelson, Volker Springel, Annalisa Pillepich +11
We present the full public release of all data from the TNG50, TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gra…
Jellyfish galaxies with the IllustrisTNG simulations: I. Gas-stripping phenomena in the full cosmological context
Kiyun Yun, Annalisa Pillepich, Elad Zinger +8
We use IllustrisTNG, a suite of gravity and MHD simulations, to study the demographics and properties of jellyfish galaxies in the full cosmological context. By jellyfish galaxies,…
Early-type galaxy density profiles from IllustrisTNG: I. Galaxy correlations and the impact of baryons
Yunchong Wang, Mark Vogelsberger, Dandan Xu +10
We explore the isothermal total density profiles of early-type galaxies (ETGs) in the IllustrisTNG simulation. For the selected 559 ETGs at with stellar mass $10^{10.7}\mat…
Atomic hydrogen in IllustrisTNG galaxies: the impact of environment parallelled with local 21-cm surveys
Adam R. H. Stevens, Benedikt Diemer, Claudia del P. Lagos +8
We investigate the influence of environment on the cold-gas properties of galaxies at z=0 within the TNG100 cosmological, magnetohydrodynamic simulation, part of the IllustrisTNG s…
A Deep Learning Approach to Galaxy Cluster X-ray Masses
M. Ntampaka, J. ZuHone, D. Eisenstein +9
We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool…