English

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

Machine Learning 2022-04-13 v1 Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics Computer Vision and Pattern Recognition

Abstract

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 \sim100 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.

Keywords

Cite

@article{arxiv.2109.10915,
  title  = {The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence},
  author = {Francisco Villaescusa-Navarro and Shy Genel and Daniel Angles-Alcazar and Leander Thiele and Romeel Dave and Desika Narayanan and Andrina Nicola and Yin Li and Pablo Villanueva-Domingo and Benjamin Wandelt and David N. Spergel and Rachel S. Somerville and Jose Manuel Zorrilla Matilla and Faizan G. Mohammad and Sultan Hassan and Helen Shao and Digvijay Wadekar and Michael Eickenberg and Kaze W. K. Wong and Gabriella Contardo and Yongseok Jo and Emily Moser and Erwin T. Lau and Luis Fernando Machado Poletti Valle and Lucia A. Perez and Daisuke Nagai and Nicholas Battaglia and Mark Vogelsberger},
  journal= {arXiv preprint arXiv:2109.10915},
  year   = {2022}
}

Comments

17 pages, 1 figure. Third paper of a series of four. Hundreds of thousands of labeled 2D maps and 3D grids from thousands of simulated universes publicly available at https://camels-multifield-dataset.readthedocs.io

R2 v1 2026-06-24T06:13:43.768Z