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The CAMELS Project: Public Data Release

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

in Astrophysics / Cosmology / Distribution functions / Dynamical systems / Galactic halos / Galaxies / Galaxy distribution / Lyman spectra / Machine learning / Many body problem / Power spectra / Probability distribution / Probability distribution functions / Simulation

2023

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2023

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2023

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Journal Article

The CAMELS Project: Public Data Release

Steinwandel, Ulrich P,

Eickenberg, Michael,

Genel, Shy,

Oppenheimer, Benjamin D,

Wandelt, Benjamin,

Perez, Lucia A,

Thiele, Leander,

La Torre, Valentina,

Mohammad, Faizan G,

Viel, Matteo,

Wadekar, Digvijay,

Li, Yin,

Kraljic, Katarina,

Burkhart, Blakesley,

Delgado, Ana Maria,

Bryan, Greg L,

Moser, Emily,

Jo, Yongseok,

Nagai, Daisuke,

Somerville, Rachel S,

Hernquist, Lars,

Marinacci, Federico,

Philcox, Oliver H. E,

Tillman, Megan,

Kaushal, Neerav,

Pisani, Alice,

Hassan, Sultan,

Lau, Erwin T,

Narayanan, Desika,

Villaescusa-Navarro, Francisco,

Coulton, William R,

Parimbelli, Gabriele,

Hahn, ChangHoon,

Caliendo, Joyce,

Wong, Kaze W. K,

Battaglia, Nicholas,

Villanueva-Domingo, Pablo,

Gebhardt, Matthew,

Nicola, Andrina,

Vogelsberger, Mark,

Anglés-Alcázar, Daniel,

Irsic, Vid,

Ni, Yueying,

Spergel, David N,

Dave, Romeel,

Machado Poletti Valle, Luis Fernando,

Kreisch, Christina,

Shao, Helen

2023

Overview

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.

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Publisher

IOP Publishing

Subject

Astrophysics

/ Cosmology

/ Distribution functions

/ Dynamical systems

/ Galactic halos

/ Galaxies

/ Galaxy distribution