%0 Journal Article
%@ 2197-7909
%A Nelson, Dylan
%A Springel, Volker
%A Pillepich, Annalisa
%A Rodriguez-Gomez, Vicente
%A Torrey, Paul
%A Genel, Shy
%A Vogelsberger, Mark
%A Pakmor, Ruediger
%A Marinacci, Federico
%A Weinberger, Rainer
%A Kelley, Luke
%A Lovell, Mark
%A Diemer, Benedikt
%A Hernquist, Lars
%C New York
%D 2019
%F heidok:26446
%I Springer international
%J Computational Astrophysics and Cosmology
%K Methods: data analysis; Methods: numerical; Galaxies: formation; Galaxies: evolution; Data management systems; Data access methods; Distributed architectures
%N 2
%P 1-29
%T The IllustrisTNG simulations: public data release
%U https://archiv.ub.uni-heidelberg.de/volltextserver/26446/
%V 6
%X We present the full public release of all data from the TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gravo-magnetohydrodynamical simulations run with the moving-mesh code Arepo. TNG includes a comprehensive model for galaxy formation physics, and each TNG simulation self-consistently solves for the coupled evolution of dark matter, cosmic gas, luminous stars, and supermassive black holes from early time to the present day, z = 0 $z=0$. Each of the flagship runs—TNG50, TNG100, and TNG300—are accompanied by halo/subhalo catalogs, merger trees, lower-resolution and dark-matter only counterparts, all available with 100 snapshots. We discuss scientific and numerical cautions and caveats relevant when using TNG. The data volume now directly accessible online is ∼750 TB, including 1200 full volume snapshots and ∼80,000 high time-resolution subbox snapshots. This will increase to ∼1.1 PB with the future release of TNG50. Data access and analysis examples are available in IDL, Python, and Matlab. We describe improvements and new functionality in the web-based API, including on-demand visualization and analysis of galaxies and halos, exploratory plotting of scaling relations and other relationships between galactic and halo properties, and a new JupyterLab interface. This provides an online, browser-based, near-native data analysis platform enabling user computation with local access to TNG data, alleviating the need to download large datasets.