arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2201.01300astro-ph.COastro-ph.GAastro-ph.IMcs.AIcs.LG
收藏

CAMELS项目:公开数据发布

The CAMELS project: public data release

Flatiron Institute(熨斗研究所);Princeton University(普林斯顿大学);Columbia University(哥伦比亚大学);University of Connecticut(康涅狄格大学);Arizona State University(亚利桑那州立大学);Instituto de Física Corpuscular (IFIC), CSIC-Universitat de València(科珀斯库尔物理研究所(IFIC),西班牙国家研究委员会-瓦伦西亚大学);New York University(纽约大学);Institute for Advanced Study(高等研究院);University of Waterloo(滑铁卢大学)
Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G. Mohammad, Sul… 展开作者

Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G. Mohammad, Sultan Hassan, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Mark Vogelsberger

AI总结:

CAMELS项目发布包含4233个宇宙学模拟、超过350TB数据及星系目录等多样化数据产品,并提供完整访问与处理文档,以支持宇宙学与天体物理学的机器学习研究。

摘要:

宇宙学与天体物理学机器学习模拟(CAMELS)项目旨在通过数千个宇宙学流体动力学模拟和机器学习,将宇宙学与天体物理学相结合。CAMELS包含4,233个宇宙学模拟,其中2,049个N体模拟和2,184个最先进的流体动力学模拟,在参数空间中采样了广阔的体积。本文介绍了CAMELS公开数据发布,描述了CAMELS模拟的特征以及由其生成的各种数据产品,包括晕、子晕、星系和空洞目录、功率谱、双谱、莱曼-α谱、概率分布函数、晕径向轮廓以及X射线光子列表。我们还发布了来自CAMELS-SAM的一千多个目录,其中包含数十亿个星系:CAMELS-SAM是一个大型N体模拟集合,已与圣克鲁斯半解析模型相结合。我们发布了所有数据,总计超过350太字节,包含143,922个快照、数百万个晕、星系和汇总统计量。我们提供了有关如何访问、下载、读取和处理数据的技术细节,详见\url{https://camels.readthedocs.io}。

英文摘要:

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}.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑