CAMELS多场数据集:利用人工智能学习宇宙基本参数 (The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence)

Francisco Villaescusa-Navarro,Shy Genel,Daniel Angles-Alcazar,Leander Thiele,Romeel Dave,Desika Narayanan,Andrina Nicola,Yin Li,Pablo Villanueva-Domingo,Benjamin Wandelt,David N. Spergel,Rachel S. Somerville,Jose Manuel Zorrilla Matilla,Faizan G. Mohammad,Sultan Hassan,Helen Shao,Digvijay Wadekar,Michael Eickenberg,Kaze W. K. Wong,Gabriella Contardo,Yongseok Jo,Emily Moser,Erwin T. Lau,Luis Fernando Machado Poletti Valle,Lucia A. Perez,Daisuke Nagai,Nicholas Battaglia,Mark Vogelsberger

from arxiv, 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

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.

翻译：我们用MachinE学习模拟多场数据集、CMD、数十万张二维地图和三维格网格的集成、包含宇宙气体、暗物质和来自多个宇宙时代2 000个不同模拟宇宙的恒星的许多不同特性。2D地图和3D网格代表宇宙区域,这些宇宙区域跨越1亿美元光年,来自CAMELS项目上千个最先进的流体动力学和重力专用N-体模拟。CMD设计用于培训机器学习模型,是其中最大的数据集,含有70多个Terabytes的数据。在本文中,我们详细描述CMD,并概述了其几个应用。我们集中关注其中一项任务,即参数推理,提出我们面对的问题,作为社区的挑战。我们在 https://camels-Multifield-dataset.readthedocs.io上公布所有数据,并提供进一步的技术细节。