Indra: a Public Computationally Accessible Suite of Cosmological $N$-body Simulations

TL;DR

Indra is a publicly accessible suite of large-volume cosmological N-body simulations designed to provide detailed statistical data on dark matter distribution, supporting large-scale structure research and demonstrating data accessibility.

Contribution

It introduces a comprehensive, publicly available set of 384 high-resolution cosmological simulations with extensive data products and analysis tools.

Findings

Measured ensemble averages, variances, and covariances of key cosmological statistics.

Demonstrated the utility of Indra data for large-scale structure research.

Showcased how to make large datasets publicly accessible and computationally usable.

Abstract

Indra is a suite of large-volume cosmological $N$-body simulations with the goal of providing excellent statistics of the large-scale features of the distribution of dark matter. Each of the 384 simulations is computed with the same cosmological parameters and different initial phases, with 1024$^3$ dark matter particles in a box of length 1 Gpc/h, 64 snapshots of particle data and halo catalogs, and 505 time steps of the Fourier modes of the density field, amounting to almost a petabyte of data. All of the Indra data are immediately available for analysis via the SciServer science platform, which provides interactive and batch computing modes, personal data storage, and other hosted data sets such as the Millennium simulations and many astronomical surveys. We present the Indra simulations, describe the data products and how to access them, and measure ensemble averages, variances, and covariances of the matter power spectrum, the matter correlation function, and the halo mass function to demonstrate the types of computations that Indra enables. We hope that Indra will be both a resource for large-scale structure research and a demonstration of how to make very large datasets public and computationally accessible.