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Dataset Open Access

Nbody 3D Histograms dataset

Janis Fluri; Nathanael Perraudin


This is the N-body simulations 3D images dataset used in the following paper:
Scalable Generative Adversarial Networks for Multi-dimensional Images
Ankit Srivastava, Nathanaël Perraudin, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara
https://arxiv.org/abs/1908.05519

@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},
}

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.

If you work with this dataset, you might be interested in this code as well https://github.com/nperraud/3DcosmoGAN

Note that a the same Nbody simulation were used in this paper, but with a different way of building the histogram.
Fast Cosmic Web Simulations with Generative Adversarial Networks
Andres C Rodriguez, Tomasz Kacprzak, Aurelien Lucchi, Adam Amara, Raphael Sgier, Janis Fluri, Thomas Hofmann, Alexandre Réfrégier
https://arxiv.org/abs/1801.09070v1


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 from Rordiguez et al. 2018:

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 = 100, h = 70 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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