Collaborative Research: CDS&E: Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) to maximize the science return of next generation cosmological experiments

合作研究：CDS

• 批准号: 2108678
• 负责人: Shy Genel
• 金额: $ 29.23万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2108678&HistoricalAwards=false
• 关键词: Collaborative; Research; CDS& Cosmology; Astrophysics

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project leverages recent major advances in computational galaxy formation to produce the largest suite of cosmological simulations with full baryonic physics designed to train machine learning algorithms for a broad range of applications, including thousands of cosmological and feedback parameter variations. This project will use this unique dataset to study how to maximize the science return from next generation cosmological surveys. Although the surveys will constrain the value of the cosmological parameters with unprecedented accuracy, achieving this goal requires overcoming two major obstacles: (1) the optimal summary statistic is unknown, and (2) a lot of the information is on scales significantly affected by baryonic processes that are still poorly understood. CAMELS will (1) develop neural networks to help extract the most cosmological information, and (2) perform thousands of simulations over a wide range of parameters to quantify uncertainties in baryonic effects. All CAMELS data products will be publicly available, to enable research and engagement by the broader community. The team will work to increase the participation and success of women and underrepresented minorities by providing dedicated mentoring and early access to research, through three programs for undergraduate students: (1) a summer research program co-organized by the National Society of Black Physicists and the Simons Observatory; (2) the AstroCom NYC program, joining other mentors from the City University of New York, the American Museum of Natural History, and the Flatiron Institute; and (3) the new Colors of Astrophysics program at the University of Connecticut.Upcoming experiments such as DES, DESI, LSST, WFIRST, SKA, and Euclid will improve our understanding of fundamental physics and the origin and fate of the Universe. CAMELS will help to determine the optimal summary statistic to apply to the non-Gaussian density fields observed in most cosmological surveys, and to quantify uncertainties in subgrid models for key astrophysical processes such as feedback from stars and massive black holes, which limit the use of hydrodynamic simulations. The neural networks and thousands of simulations that will be used by CAMELS will produce a distinct qualitative improvement over previous work.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

机器学习模拟（Camels）的宇宙学和天体物理学项目利用了计算银河形成的最新进展，以制作最大的宇宙学模拟套件，其完整的Baryonic Physics旨在为机器学习算法训练广泛的应用，包括数千种宇宙学和反馈参数变化。 该项目将使用这个独特的数据集来研究如何从下一代宇宙学调查中最大化科学回报。 尽管调查将以前所未有的准确性来限制宇宙学参数的价值，但是实现此目标需要克服两个主要障碍：（1）最佳摘要统计量尚不清楚，并且（2）许多信息在量表上受到较少了解的量表的影响。 骆驼将（1）开发神经网络以帮助提取最大的宇宙学信息，（2）在广泛的参数上执行数千个模拟，以量化重男性效应的不确定性。 所有骆驼数据产品都将公开使用，以实现更广泛的社区的研究和参与。 该团队将通过为本科生的三个计划提供专门的指导和早期研究，以通过为本科生提供专门的指导和早期研究，以提高妇女和代表性不足的少数民族的参与和成功：（1）由国家黑人物理学家和西蒙斯观察员协会共同组织的夏季研究计划； （2）纽约市星系计划，加入了纽约市城市大学，美国自然历史博物馆和Flatiron Institute的其他导师； （3）康涅狄格大学的天体物理学计划的新颜色。 骆驼将有助于确定适用于大多数宇宙学调查中观察到的非高斯密度场的最佳摘要统计量，并量化关键天体物理过程的亚网格模型中的不确定性，例如来自恒星的反馈和巨大的黑洞，这限制了流体动力学模拟的使用。 骆驼将使用的神经网络和成千上万的模拟将对以前的工作产生明显的质量改进。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。

项目成果

Calibrating Cosmological Simulations with Implicit Likelihood Inference Using Galaxy Growth Observables

• DOI: 10.3847/1538-4357/aca8fe
• 发表时间: 2022-11
• 期刊: The Astrophysical Journal
• 作者: Yongseok Jo;S. Genel;Benjamin Dan Wandelt;R. Somerville;F. Villaescusa-Navarro;G. Bryan;D. Anglés-Alcázar;D. Foreman-Mackey;D. Nelson;Ji-hoon Kim

The CAMELS Project: Public Data Release

• DOI: 10.3847/1538-4365/acbf47
• 发表时间: 2022-01
• 期刊: The Astrophysical Journal Supplement Series
• 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