The Quijote simulations. (arXiv:1909.05273v1 [astro-ph.CO])
<a href="http://arxiv.org/find/astro-ph/1/au:+Villaescusa_Navarro_F/0/1/0/all/0/1">Francisco Villaescusa-Navarro</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Hahn_C/0/1/0/all/0/1">ChangHoon Hahn</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Massara_E/0/1/0/all/0/1">Elena Massara</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Banerjee_A/0/1/0/all/0/1">Arka Banerjee</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Delgado_A/0/1/0/all/0/1">Ana Maria Delgado</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ramanah_D/0/1/0/all/0/1">Doogesh Kodi Ramanah</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Charnock_T/0/1/0/all/0/1">Tom Charnock</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Giusarma_E/0/1/0/all/0/1">Elena Giusarma</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Li_Y/0/1/0/all/0/1">Yin Li</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Allys_E/0/1/0/all/0/1">Erwan Allys</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Brochard_A/0/1/0/all/0/1">Antoine Brochard</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Chiang_C/0/1/0/all/0/1">Chi-Ting Chiang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+He_S/0/1/0/all/0/1">Siyu He</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Pisani_A/0/1/0/all/0/1">Alice Pisani</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Obuljen_A/0/1/0/all/0/1">Andrej Obuljen</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Feng_Y/0/1/0/all/0/1">Yu Feng</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Castorina_E/0/1/0/all/0/1">Emanuele Castorina</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Contardo_G/0/1/0/all/0/1">Gabriella Contardo</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Kreisch_C/0/1/0/all/0/1">Christina D. Kreisch</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Nicola_A/0/1/0/all/0/1">Andrina Nicola</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Scoccimarro_R/0/1/0/all/0/1">Roman Scoccimarro</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Verde_L/0/1/0/all/0/1">Licia Verde</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Viel_M/0/1/0/all/0/1">Matteo Viel</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ho_S/0/1/0/all/0/1">Shirley Ho</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Mallat_S/0/1/0/all/0/1">Stephane Mallat</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Wandelt_B/0/1/0/all/0/1">Benjamin Wandelt</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Spergel_D/0/1/0/all/0/1">David N. Spergel</a>

The Quijote simulations are a set of 43100 full N-body simulations spanning
more than 7000 cosmological models in the ${Omega_{rm m}, Omega_{rm b}, h,
n_s, sigma_8, M_nu, w }$ hyperplane. At a single redshift the simulations
contain more than 8.5 trillions of particles over a combined volume of 43100
$(h^{-1}{rm Gpc})^3$. Billions of dark matter halos and cosmic voids have been
identified in the simulations, whose runs required more than 35 million core
hours. The Quijote simulations have been designed for two main purposes: 1) to
quantify the information content on cosmological observables, and 2) to provide
enough data to train machine learning algorithms. In this paper we describe the
simulations and show a few of their applications. We also release the Petabyte
of data generated, comprising hundreds of thousands of simulation snapshots at
multiple redshifts, halo and void catalogs, together with millions of summary
statistics such as power spectra, bispectra, correlation functions, marked
power spectra, and estimated probability density functions.

The Quijote simulations are a set of 43100 full N-body simulations spanning
more than 7000 cosmological models in the ${Omega_{rm m}, Omega_{rm b}, h,
n_s, sigma_8, M_nu, w }$ hyperplane. At a single redshift the simulations
contain more than 8.5 trillions of particles over a combined volume of 43100
$(h^{-1}{rm Gpc})^3$. Billions of dark matter halos and cosmic voids have been
identified in the simulations, whose runs required more than 35 million core
hours. The Quijote simulations have been designed for two main purposes: 1) to
quantify the information content on cosmological observables, and 2) to provide
enough data to train machine learning algorithms. In this paper we describe the
simulations and show a few of their applications. We also release the Petabyte
of data generated, comprising hundreds of thousands of simulation snapshots at
multiple redshifts, halo and void catalogs, together with millions of summary
statistics such as power spectra, bispectra, correlation functions, marked
power spectra, and estimated probability density functions.

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