TY - JOUR
T1 - The CAMELS Project
T2 - Public Data Release
AU - Villaescusa-Navarro, Francisco
AU - Genel, Shy
AU - Anglés-Alcázar, Daniel
AU - Perez, Lucia A.
AU - Villanueva-Domingo, Pablo
AU - Wadekar, Digvijay
AU - Shao, Helen
AU - Mohammad, Faizan G.
AU - Hassan, Sultan
AU - Moser, Emily
AU - Lau, Erwin T.
AU - Machado Poletti Valle, Luis Fernando
AU - Nicola, Andrina
AU - Thiele, Leander
AU - Jo, Yongseok
AU - Philcox, Oliver H.E.
AU - Oppenheimer, Benjamin D.
AU - Tillman, Megan
AU - Hahn, Chang Hoon
AU - Kaushal, Neerav
AU - Pisani, Alice
AU - Gebhardt, Matthew
AU - Delgado, Ana Maria
AU - Caliendo, Joyce
AU - Kreisch, Christina
AU - Wong, Kaze W.K.
AU - Coulton, William R.
AU - Eickenberg, Michael
AU - Parimbelli, Gabriele
AU - Ni, Yueying
AU - Steinwandel, Ulrich P.
AU - La Torre, Valentina
AU - Dave, Romeel
AU - Battaglia, Nicholas
AU - Nagai, Daisuke
AU - Spergel, David N.
AU - Hernquist, Lars
AU - Burkhart, Blakesley
AU - Narayanan, Desika
AU - Wandelt, Benjamin
AU - Somerville, Rachel S.
AU - Bryan, Greg L.
AU - Viel, Matteo
AU - Li, Yin
AU - Irsic, Vid
AU - Kraljic, Katarina
AU - Marinacci, Federico
AU - Vogelsberger, Mark
N1 - Publisher Copyright:
© 2023. The Author(s). Published by the American Astronomical Society.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - 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.
AB - 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.
KW - Astrostatistics
KW - Cosmology
KW - Galaxy formation
KW - Hydrodynamical simulations
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U2 - 10.3847/1538-4365/acbf47
DO - 10.3847/1538-4365/acbf47
M3 - Article
AN - SCOPUS:85152545973
SN - 0067-0049
VL - 265
JO - Astrophysical Journal, Supplement Series
JF - Astrophysical Journal, Supplement Series
IS - 2
M1 - 54
ER -