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 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io.
The CAMELS Project: Public Data Release / Villaescusa-Navarro, Francisco; Genel, Shy; Anglés-Alcázar, Daniel; Perez, Lucia A.; Villanueva-Domingo, Pablo; Wadekar, Digvijay; Shao, Helen; Mohammad, Faizan G.; Hassan, Sultan; Moser, Emily; Lau, Erwin T.; Fernando Machado Poletti Valle, Luis; Nicola, Andrina; Thiele, Leander; Jo, Yongseok; Philcox, Oliver H. E.; Oppenheimer, Benjamin D.; Tillman, Megan; Hahn, Changhoon; Kaushal, Neerav; Pisani, Alice; Gebhardt, Matthew; Maria Delgado, Ana; Caliendo, Joyce; Kreisch, Christina; Wong, Kaze W. K.; Coulton, William R.; Eickenberg, Michael; Parimbelli, Gabriele; Ni, Yueying; Steinwandel, Ulrich P.; La Torre, Valentina; Dave, Romeel; Battaglia, Nicholas; Nagai, Daisuke; Spergel, David N.; Hernquist, Lars; Burkhart, Blakesley; Narayanan, Desika; Wandelt, Benjamin; Somerville, Rachel S.; Bryan, Greg L.; Viel, Matteo; Li, Yin; Irsic, Vid; Kraljic, Katarina; Marinacci, Federico; Vogelsberger, Mark Philipp. - In: ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES. - ISSN 0067-0049. - 265:2(2023), pp. 1-14. [10.3847/1538-4365/acbf47]
The CAMELS Project: Public Data Release
Oliver H. E. Philcox;William R. Coulton;Gabriele Parimbelli;Matteo Viel;Vid Irsic;Mark Vogelsberger
2023-01-01
Abstract
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 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io.File | Dimensione | Formato | |
---|---|---|---|
Villaescusa-Navarro_2023_ApJS_265_54.pdf
accesso aperto
Descrizione: pdf editoriale
Licenza:
Creative commons
Dimensione
1.31 MB
Formato
Adobe PDF
|
1.31 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.