%0 Generic %1 villaescusanavarro2019quijote %A Villaescusa-Navarro, Francisco %A Hahn, ChangHoon %A Massara, Elena %A Banerjee, Arka %A Delgado, Ana Maria %A Ramanah, Doogesh Kodi %A Charnock, Tom %A Giusarma, Elena %A Li, Yin %A Allys, Erwan %A Brochard, Antoine %A Chiang, Chi-Ting %A He, Siyu %A Pisani, Alice %A Obuljen, Andrej %A Feng, Yu %A Castorina, Emanuele %A Contardo, Gabriella %A Kreisch, Christina D. %A Nicola, Andrina %A Scoccimarro, Roman %A Verde, Licia %A Viel, Matteo %A Ho, Shirley %A Mallat, Stephane %A Wandelt, Benjamin %A Spergel, David N. %D 2019 %K tifr %T The Quijote simulations %U http://arxiv.org/abs/1909.05273 %X The Quijote simulations are a set of 43100 full N-body simulations spanning more than 7000 cosmological models in the $\Ømega_m, Ømega_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 $(h^-1Gpc)^3$. 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.

@misc{villaescusanavarro2019quijote, abstract = {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.}, added-at = {2019-09-13T06:56:34.000+0200}, author = {Villaescusa-Navarro, Francisco and Hahn, ChangHoon and Massara, Elena and Banerjee, Arka and Delgado, Ana Maria and Ramanah, Doogesh Kodi and Charnock, Tom and Giusarma, Elena and Li, Yin and Allys, Erwan and Brochard, Antoine and Chiang, Chi-Ting and He, Siyu and Pisani, Alice and Obuljen, Andrej and Feng, Yu and Castorina, Emanuele and Contardo, Gabriella and Kreisch, Christina D. and Nicola, Andrina and Scoccimarro, Roman and Verde, Licia and Viel, Matteo and Ho, Shirley and Mallat, Stephane and Wandelt, Benjamin and Spergel, David N.}, biburl = {https://www.bibsonomy.org/bibtex/25d7747ff28390fd6d4ffe6b0337ecb3f/citekhatri}, description = {The Quijote simulations}, interhash = {f35475785722f1d80c23a5dc7e442f83}, intrahash = {5d7747ff28390fd6d4ffe6b0337ecb3f}, keywords = {tifr}, note = {cite arxiv:1909.05273Comment: 19 pages, 15 figures. Simulations publicly available at https://github.com/franciscovillaescusa/Quijote-simulations}, timestamp = {2019-09-13T06:56:34.000+0200}, title = {The Quijote simulations}, url = {http://arxiv.org/abs/1909.05273}, year = 2019 }