Dataset Open Access

# Nbody 3D Histograms dataset

Janis Fluri; Nathanael Perraudin

3Dcosmo: a benchmark dataset for large 3-dimensional generative models (and 2-dimensional as well)

This is the N-body simulations 3D images dataset used in the paper Cosmological N-body simulations: a challenge for scalable generative models, Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier

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.

3DCosmo benchmark

This dataset can be used to evaluate 2D and 3D generative model. It is particularly suitable for large scale 3D images. Please check https://github.com/nperraud/3DcosmoGAN for more information.

Please consider citing our paper if you use it.

@inproceedings{perraudin2019cosmological,
title = {Cosmological N-body simulations: a challenge for scalable generative models},
author = {Nathana\"el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
year = {2019},
archivePrefix = {arXiv},
eprint = {1908.05519},
url = {https://arxiv.org/abs/1908.05519},
}


While this data is associated to the paper Cosmological N-body simulations: a challenge for scalable generative models, note that a the same Nbody simulation were used in the paper Fast Cosmic Web Simulations with Generative Adversarial Networks (https://arxiv.org/abs/1801.09070v1), but with a different way of building the histogram. You may want to cite this work as well.

@article{rodriguez2018fast,
title={Fast cosmic web simulations with generative adversarial networks},
author={Rodr{\'\i}guez, Andres C and Kacprzak, Tomasz and Lucchi, Aurelien and Amara, Adam and Sgier, Rapha{\"e}l and Fluri, Janis and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
journal={Computational Astrophysics and Cosmology},
volume={5},
number={1},
pages={4},
year={2018},
publisher={Springer}
}


N-body simulation evolves a cosmological matter distribution over time, starting from soon after the big bang. It represents matter density distribution as a finite set of massive particles, typically order of trillions. The positions of these particles are modified due to gravitational forces and expansion of the cosmological volume due to cosmic acceleration. N-body simulations use periodic boundary condition, where particles leaving the volume on one face enter it back from the opposite side.

Short description of the data generation:

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. We used L-PICOLA [21] to create 10 and 30 independent simulation boxes for both box sizes. The cosmological model used was ΛCDM (Cold Dark Matter) with Hubble constant H0 = 500, h = 350 km s−1 Mpc−1, dark energy density Omega_Lambda = 0.72 and matter density Omega_m = 0.28. We used the particle distribution at redshift z = 0.

For additional information, please check the README.md

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