The DOI matches its Crossref record; 121 of the 121 references it cites were found in a registry or an index.
The IllustrisTNG simulations: public data release
Open accessAbstract
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.
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Cited by
Pillepich, A., Nelson, D., Springel, V., Pakmor, R., Torrey, P., Weinberger, R., Vogelsberger, M., Marinacci, F., Genel, S., van der Wel, A., et al. (2019) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stz2338 · Cited by 916
Self-citationStreams, Substructures, and the Early History of the Milky Way
Helmi, A. (2020) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev-astro-032620-021917 · Cited by 407
The Cosmic Baryon and Metal Cycles
Péroux, C., & Howk, J. C. (2020) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev-astro-021820-120014 · Cited by 322
The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations
Villaescusa-Navarro, F., Anglés-Alcázar, D., Genel, S., Spergel, D. N., S. Somerville, R., Dave, R., Pillepich, A., Hernquist, L., Nelson, D., Torrey, P., et al. (2021) · The Astrophysical Journal · doi:10.3847/1538-4357/abf7ba · Cited by 304
Self-citationCurti, M., D’Eugenio, F., Carniani, S., Maiolino, R., Sandles, L., Witstok, J., Baker, W. M., Bennett, J. S., Piotrowska, J. M., Tacchella, S., et al. (2022) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stac2737 · Cited by 282
Metadata
- Authors
- Nelson, D., Springel, V., Pillepich, A., Rodriguez-Gomez, V., Torrey, P., Genel, S., Vogelsberger, M., Pakmor, R., Marinacci, F., Weinberger, R., Kelley, L., Lovell, M., Diemer, B., & Hernquist, L.
- Venue
- Computational Astrophysics and Cosmology
- Published
- 2019-05-14
- Volume
- 6
- Issue
- 1
- ISSN
- 2197-7909 (ISSN-L)
- OpenAlex
- W2904186977
- Cited by
- 1,436
- References
- 121
- FWCI
- 70.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
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