The CAMELS Project: Public Data Release

The CAMELS Project: Public Data Release
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DOI：
10.3847/1538-4365/acbf47
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发表时间：
2022-01
期刊：
The Astrophysical Journal Supplement Series
影响因子：
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通讯作者：
F. Villaescusa-Navarro;S. Genel;D. Angl'es-Alc'azar;L. A. Perez;Pablo Villanueva-Domingo;D. Wadekar;Helen Shao;F. G. Mohammad;Sultan Hassan;E. Moser;E. Lau;Luis Fernando Machado Poletti Valle;A. Nicola;L. Thiele;Yongseok Jo;O. Philcox;B. Oppenheimer;M. Tillman;C. Hahn;Neerav Kaushal;A. Pisani;M. Gebhardt;Ana Maria Delgado;J. Caliendo;C. Kreisch;Ka-wah Wong;W. Coulton;Michael Eickenberg;G. Parimbelli;Y. Ni;U. Steinwandel;V. L. Torre;R. Davé;N. Battaglia;D. Nagai;D. Spergel;L. Hernquist;B. Burkhart;D. Narayanan;Benjamin Dan Wandelt;R. Somerville;G. Bryan;M. Viel;Yin Li;V. Iršič;K. Kraljic;M. Vogelsberger
F. Villaescusa-Navarro;S. Genel;D. Angl'es-Alc'azar;L. A. Perez;Pablo Villanueva-Domingo;D. Wadekar;Helen Shao;F. G. Mohammad;Sultan Hassan;E. Moser;E. Lau;Luis Fernando Machado Poletti Valle;A. Nicola;L. Thiele;Yongseok Jo;O. Philcox;B. Oppenheimer;M. Tillman;C. Hahn;Neerav Kaushal;A. Pisani;M. Gebhardt;Ana Maria Delgado;J. Caliendo;C. Kreisch;Ka-wah Wong;W. Coulton;Michael Eickenberg;G. Parimbelli;Y. Ni;U. Steinwandel;V. L. Torre;R. Davé;N. Battaglia;D. Nagai;D. Spergel;L. Hernquist;B. Burkhart;D. Narayanan;Benjamin Dan Wandelt;R. Somerville;G. Bryan;M. Viel;Yin Li;V. Iršič;K. Kraljic;M. Vogelsberger
中科院分区：
其他
文献类型：
--
作者：
F. Villaescusa-Navarro;S. Genel;D. Angl'es-Alc'azar;L. A. Perez;Pablo Villanueva-Domingo;D. Wadekar;Helen Shao;F. G. Mohammad;Sultan Hassan;E. Moser;E. Lau;Luis Fernando Machado Poletti Valle;A. Nicola;L. Thiele;Yongseok Jo;O. Philcox;B. Oppenheimer;M. Tillman;C. Hahn;Neerav Kaushal;A. Pisani;M. Gebhardt;Ana Maria Delgado;J. Caliendo;C. Kreisch;Ka-wah Wong;W. Coulton;Michael Eickenberg;G. Parimbelli;Y. Ni;U. Steinwandel;V. L. Torre;R. Davé;N. Battaglia;D. Nagai;D. Spergel;L. Hernquist;B. Burkhart;D. Narayanan;Benjamin Dan Wandelt;R. Somerville;G. Bryan;M. Viel;Yin Li;V. Iršič;K. Kraljic;M. Vogelsberger

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利用机器学习模拟的宇宙学和天体物理学（camel）项目是为了将宇宙学和天体物理学结合起来而开发的，通过成千上万的宇宙流体动力学模拟和机器学习。camel包含4233个宇宙学模拟，2049个n体模拟和2184个最先进的流体动力学模拟，在参数空间中采样大量。在本文中，我们介绍了camel的公开数据发布，描述了camel模拟的特点以及由此产生的各种数据产品，包括光晕，亚光晕，星系和空洞目录，功率谱，双光谱，Lyα光谱，概率分布函数，光晕径向剖面和x射线光子列表。我们还发布了1000多个目录，其中包含来自CAMELS-SAM的数十亿个星系：这是一个大型n体模拟集合，与圣克鲁斯半分析模型相结合。我们发布了所有数据，包括超过350tb的数据，包含143922个快照，数百万个光晕，星系和汇总统计数据。我们在https://camels.readthedocs.io上提供了关于如何访问、下载、读取和处理数据的进一步技术细节。
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 4233 cosmological simulations, 2049 N-body simulations, and 2184 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 catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic 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 https://camels.readthedocs.io.