Neerav Kaushal

Scientist II, Deep Learning



Sail Biomedicines (Flagship Pioneering)



The CAMELS Project: Public Data Release


Journal article


F. Villaescusa-Navarro, S. Genel, D. Angl'es-Alc'azar, L. A. Perez, Pablo Villanueva-Domingo, D. Wadekar, Helen Shao, F. G. Mohammad, Sultan Hassan, E. Moser, E. Lau, Luis Fernando Machado Poletti Valle, A. Nicola, L. Thiele, Yongseok Jo, O. Philcox, B. Oppenheimer, M. Tillman, C. Hahn, Neerav Kaushal, A. Pisani, M. Gebhardt, Ana Maria Delgado, J. Caliendo, C. Kreisch, Ka-wah Wong, W. Coulton, Michael Eickenberg, G. Parimbelli, Y. Ni, U. Steinwandel, V. L. Torre, R. Davé, N. Battaglia, D. Nagai, D. Spergel, L. Hernquist, B. Burkhart, D. Narayanan, Benjamin Dan Wandelt, R. Somerville, G. Bryan, M. Viel, Yin Li, V. Iršič, K. Kraljic, M. Vogelsberger
Astrophysical Journal Supplement Series, 2022

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APA   Click to copy
Villaescusa-Navarro, F., Genel, S., Angl'es-Alc'azar, D., Perez, L. A., Villanueva-Domingo, P., Wadekar, D., … Vogelsberger, M. (2022). The CAMELS Project: Public Data Release. Astrophysical Journal Supplement Series.


Chicago/Turabian   Click to copy
Villaescusa-Navarro, F., S. Genel, D. Angl'es-Alc'azar, L. A. Perez, Pablo Villanueva-Domingo, D. Wadekar, Helen Shao, et al. “The CAMELS Project: Public Data Release.” Astrophysical Journal Supplement Series (2022).


MLA   Click to copy
Villaescusa-Navarro, F., et al. “The CAMELS Project: Public Data Release.” Astrophysical Journal Supplement Series, 2022.


BibTeX   Click to copy

@article{f2022a,
  title = {The CAMELS Project: Public Data Release},
  year = {2022},
  journal = {Astrophysical Journal Supplement Series},
  author = {Villaescusa-Navarro, F. and Genel, S. and Angl'es-Alc'azar, D. and Perez, L. A. and Villanueva-Domingo, Pablo and Wadekar, D. and Shao, Helen and Mohammad, F. G. and Hassan, Sultan and Moser, E. and Lau, E. and Valle, Luis Fernando Machado Poletti and Nicola, A. and Thiele, L. and Jo, Yongseok and Philcox, O. and Oppenheimer, B. and Tillman, M. and Hahn, C. and Kaushal, Neerav and Pisani, A. and Gebhardt, M. and Delgado, Ana Maria and Caliendo, J. and Kreisch, C. and Wong, Ka-wah and Coulton, W. and Eickenberg, Michael and Parimbelli, G. and Ni, Y. and Steinwandel, U. and Torre, V. L. and Davé, R. and Battaglia, N. and Nagai, D. and Spergel, D. and Hernquist, L. and Burkhart, B. and Narayanan, D. and Wandelt, Benjamin Dan and Somerville, R. and Bryan, G. and Viel, M. and Li, Yin and Iršič, V. and Kraljic, K. and Vogelsberger, M.}
}

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.