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The CAMELS Project

Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G Mohammad, Sultan Hassan, Emily Moser, Erwin T Lau, Luis Fernando Machado Poletti Valle, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver HE Philcox, Benjamin D Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze WK Wong, William R Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin Wandelt, Rachel S Somerville, Greg L Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Federico Marinacci, Mark Vogelsberger
OAI: oai:www.repository.cam.ac.uk:1810/348429 • DOI: 10.17863/CAM.95855
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Abstract

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.