The Illustris Simulation: Public Data Release

TL;DR

The paper announces the public release of the entire dataset from the Illustris cosmological simulation, including detailed galaxy formation data, tools for analysis, and extensive documentation, enabling broad scientific use.

Contribution

It provides the first comprehensive public access to the full suite of Illustris simulation data, including multiple resolutions, snapshots, and analysis tools, facilitating further research in galaxy formation.

Findings

Release of 265 TB of simulation data

Availability of 136 redshift snapshots and merger trees

Tools and APIs for data access and analysis

Abstract

We present the full public release of all data from the Illustris simulation project. Illustris is a suite of large volume, cosmological hydrodynamical simulations run with the moving-mesh code Arepo and including a comprehensive set of physical models critical for following the formation and evolution of galaxies across cosmic time. Each simulates a volume of (106.5 Mpc)^3 and self-consistently evolves five different types of resolution elements from a starting redshift of z=127 to the present day, z=0. These components are: dark matter particles, gas cells, passive gas tracers, stars and stellar wind particles, and supermassive black holes. This data release includes the snapshots at all 136 available redshifts, halo and subhalo catalogs at each snapshot, and two distinct merger trees. Six primary realizations of the Illustris volume are released, including the flagship Illustris-1 run. These include three resolution levels with the fiducial "full" baryonic physics model, and a dark matter only analog for each. In addition, we provide four distinct, high time resolution, smaller volume "subboxes". The total data volume is ~265 TB, including ~800 full volume snapshots and ~30,000 subbox snapshots. We describe the released data products as well as tools we have developed for their analysis. All data may be directly downloaded in its native HDF5 format. Additionally, we release a comprehensive, web-based API which allows programmatic access to search and data processing tasks. In both cases we provide example scripts and a getting-started guide in several languages: currently, IDL, Python, and Matlab. This paper addresses scientific issues relevant for the interpretation of the simulations, serves as a pointer to published and on-line documentation of the project, describes planned future additional data releases, and discusses technical aspects of the release.