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Nbody 3D Histograms dataset

Janis Fluri; Nathanael Perraudin


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    "description": "<p><br>\nThis is the N-body simulations 3D images dataset used in the following paper:<br>\n<strong>Scalable Generative Adversarial Networks for Multi-dimensional Images</strong><br>\n<em>Ankit Srivastava, Nathana&euml;l Perraudin, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara</em><br>\n<a href=\"https://arxiv.org/abs/1908.05519\">https://arxiv.org/abs/1908.05519</a></p>\n\n<blockquote>\n<p>@inproceedings{perraudin2019cosmological,<br>\n&nbsp; title = {Cosmological N-body simulations: a challenge for scalable generative models},<br>\n&nbsp; author = {Nathana\\&quot;el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\\&#39;e}fr{\\&#39;e}gier, Alexandre},<br>\n&nbsp; year = {2019},<br>\n&nbsp; archivePrefix = {arXiv},<br>\n&nbsp; eprint = {1908.05519},<br>\n&nbsp; url = {https://arxiv.org/abs/1908.05519},<br>\n}</p>\n</blockquote>\n\n<p>The dataset does not contain the Nbody simulations as they have a very large size. Instead, we sliced the space into 256 x 256 x 256 cubical areas and counted the number of particules in each area. The result are 3D histograms, where the number of particles is a proxy for matter density.</p>\n\n<p>If you work with this dataset, you might be interested in this code as well <a href=\"https://github.com/nperraud/3DcosmoGAN\">https://github.com/nperraud/3DcosmoGAN</a></p>\n\n<p>Note that a the same Nbody simulation were used in this paper, but with a different way of building the histogram.<br>\n<strong>Fast Cosmic Web Simulations with Generative Adversarial Networks</strong><br>\n<em>Andres C Rodriguez, Tomasz Kacprzak, Aurelien Lucchi, Adam Amara, Raphael Sgier, Janis Fluri, Thomas Hofmann, Alexandre R&eacute;fr&eacute;gier</em><br>\n<a href=\"https://arxiv.org/abs/1801.09070v1\">https://arxiv.org/abs/1801.09070v1</a></p>\n\n<p><br>\nN-body simulation evolves a cosmological matter distribution over time, starting from soon after the big bang.<br>\nIt represents matter density distribution as a finite set of massive particles, typically order of trillions.<br>\nThe positions of these particles are modified due to gravitational forces and expansion of the cosmological volume due to cosmic acceleration.<br>\nN-body simulations use periodic boundary condition, where particles leaving the volume on one face enter it back from the opposite side.</p>\n\n<p>## Short description of the data generation from Rordiguez et al. 2018:</p>\n\n<p>We created N-body simulations of cosmic structures in boxes of size 100 Mpc and 500 Mpc with 512^3 and 1,024^3 particles respectively.<br>\nWe used L-PICOLA [21] to create 10 and 30 independent simulation boxes for both box sizes.<br>\nThe cosmological model used was &Lambda;CDM (Cold Dark Matter) with Hubble constant H0 = 100, h = 70 km s&minus;1 Mpc&minus;1,<br>\ndark energy density Omega_Lambda = 0.72 and matter density Omega_m = 0.28.<br>\nWe used the particle distribution at redshift z = 0.</p>\n\n<p><br>\nFor additional information, please check the README.md</p>", 
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    "title": "Nbody 3D Histograms dataset", 
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        "affiliation": "Cosmology Research Group - ETHZ", 
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