The FLAMINGO simulations data release

TL;DR

This paper announces the public release of over 2.3 petabytes of data from the FLAMINGO cosmological simulations, including hydrodynamical and gravity-only runs with various parameters and resolutions.

Contribution

It provides a comprehensive data set from state-of-the-art cosmological simulations, including new unpublished runs with varied cosmologies and dark matter models.

Findings

Simulations calibrated to match galaxy stellar mass functions and gas fractions.

Includes multiple resolutions and cosmological parameters, including neutrino masses.

Provides tools for selective data access due to large data volume.

Abstract

We describe the public release of $>2.3$ petabytes of data from the FLAMINGO cosmological simulations. The suite consists of hydrodynamical simulations that include radiative cooling, star formation, stellar mass loss and the resulting chemical enrichment, supernova feedback, and two implementations of AGN feedback. Neutrinos are simulated explicitly using particles. Data products include snapshots, halo and galaxy catalogues, HEALPix all-sky lightcone maps, particle data for lightcone maps, and power spectra. The FLAMINGO set includes 22 hydrodynamical simulations. In addition, there are 16 gravity-only simulations, including the $10080^3$ particles FLAMINGO-10k run, with initial conditions that match those of the corresponding hydrodynamical runs. The fiducial hydrodynamical simulations span three numerical resolutions that have each been calibrated to reproduce the present-day galaxy stellar mass function and gas fractions in low-redshift clusters. Other simulations systematically vary the galaxy stellar mass function, cluster gas fractions, cosmology (including neutrino masses), and/or the nature of dark matter, in volumes of 1Gpc$^3$. The release includes hitherto unpublished simulations that use extra dark matter particles. While we provide a facility for downloading complete simulation outputs, we recognise that for many users this will not be possible due to limited local storage or network bandwidth. We implement a web service that enables users to explore available outputs and selectively download datasets or parts of datasets.