Kavli Affiliate: David N. Spergel
| First 5 Authors: Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, Leander Thiele, Romeel Dave
| Summary:
We present the Cosmology and Astrophysics with MachinE Learning Simulations
(CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D
maps and 3D grids containing many different properties of cosmic gas, dark
matter, and stars from 2,000 distinct simulated universes at several cosmic
times. The 2D maps and 3D grids represent cosmic regions that span $sim$100
million light years and have been generated from thousands of state-of-the-art
hydrodynamic and gravity-only N-body simulations from the CAMELS project.
Designed to train machine learning models, CMD is the largest dataset of its
kind containing more than 70 Terabytes of data. In this paper we describe CMD
in detail and outline a few of its applications. We focus our attention on one
such task, parameter inference, formulating the problems we face as a challenge
to the community. We release all data and provide further technical details at
https://camels-multifield-dataset.readthedocs.io.
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