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The CAMELS project: public data release

Authors :
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.
Valle, Luis Fernando Machado Poletti
Nicola, Andrina
Thiele, Leander
Jo, Yongseok
Philcox, Oliver H. E.
Oppenheimer, Benjamin D.
Tillman, Megan
Hahn, ChangHoon
Kaushal, Neerav
Pisani, Alice
Gebhardt, Matthew
Delgado, Ana Maria
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
Vogelsberger, Mark
Publication Year :
2022

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 4,233 cosmological simulations, 2,049 N-body and 2,184 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 catalogues, power spectra, bispectra, Lyman-$\alpha$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic 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 \url{https://camels.readthedocs.io}.<br />Comment: 18 pages, 3 figures. More than 350 Tb of data from thousands of simulations publicly available at https://www.camel-simulations.org

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2201.01300
Document Type :
Working Paper
Full Text :
https://doi.org/10.3847/1538-4365/acbf47