论文标题
部分可观测时空混沌系统的无模型预测
The CAMELS project: public data release
论文作者
论文摘要
带有机器学习模拟（骆驼）项目的宇宙学和天体物理学是通过数千种宇宙学水动力模拟和机器学习结合宇宙学与天体物理学结合的。骆驼包含4,233个宇宙学模拟，2,049个N体和2,184个最先进的流体动力模拟，这些模拟在参数空间中进行了大量量。在本文中，我们介绍了骆驼公共数据发布，描述了骆驼模拟的特征以及从它们产生的各种数据产品的特征，包括Halo，Subhalo，Galaxy和Void Catalogs，Power Spectra，Bispectra，Bispectra，Lyman- $ a $α$ spectra，概率分配功能，Halo radial Profiles和X-Ray Photon列表。我们还释放了一千多个目录，其中包含来自骆驼SAM的数十亿个星系：与圣克鲁斯半分析模型相结合的大量N体模拟集合。我们释放所有数据，包括350多个Terabytes，并包含143,922张快照，数百万个光晕，星系和摘要统计数据。我们提供了有关如何访问，下载，阅读和处理数据的更多技术详细信息，请{https://camels.readthedocs.io}。
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogues, power spectra, bispectra, Lyman-$α$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic Model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies and summary statistics. We provide further technical details on how to access, download, read, and process the data at \url{https://camels.readthedocs.io}.
