Collaborative Research: Elements: Software: NSCI: HDR: Building An HPC/HTC Infrastructure For The Synthesis And Analysis Of Current And Future Cosmic Microwave Background Datasets
合作研究:要素:软件:NSCI:HDR:构建 HPC/HTC 基础设施以合成和分析当前和未来的宇宙微波背景数据集
基本信息
- 批准号:1835865
- 负责人:
- 金额:$ 48.1万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-09-01 至 2022-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The photons created in the Big Bang have experienced the entire history of the Universe, and every step in the evolution of the Universe has left its mark on their statistical properties. Observations of these photons have the potential to unlock the secrets of fundamental physics and cosmology, and to provide key insights into the formation and evolution of cosmic structures such as galaxies and galaxy clusters. Since the traces of these processes are so faint, one must gather enormous datasets to be able to detect them above the unavoidable instrumental and environmental noise. This in turn means that one must be able to use the most powerful computing resources available to be able to process the volume of data. These computing resources include both highly localized supercomputers and widely distributed grid and cloud systems. The PI and Co-Is will develop a common computing infrastructure able to take advantage of both types of resource, and demonstrate its suitability for ongoing and planned experiments by adapting the analysis pipelines of four leading Big Bang observatories to run within it. In addition to enabling the full scientific exploitation of these extraordinarily rich data sets, the investigators will mentor students engaged in this research and run summer schools in applied supercomputing.This project seeks to enable the detection of the faintest signals in Cosmic Microwave Background radiation, and in particular the pattern of peaks and troughs in the angular power spectra of its polarization field. In order to obtain these spectra one must first reduce the raw observations to maps of the sky in a way the preserve the correlations in the signal and characterizes the correlation in the noise. While the algorithms to perform this reduction are well-understood, applying them to data sets with quadrillions to quintillions of observations is a very serious computational challenge. The computational resources available to the project to address this include both high performance and high throughput computing systems, and one will need to take advantage of both of them. This project will develop a joint high performance/high throughput computational framework, and deploy within it analysis pipelines currently being fielded by the ongoing Atacama Cosmology Telescope, BICEP/Keck Array, POLARBEAR, and South Pole Telescope experiments. By doing so one will also demonstrate the frameworks efficacy for the planned Simons Observatory and CMB-S4 experiments.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Division of Astronomical Sciences in the Directorate of Mathematical and Physical Sciences.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.
大爆炸中产生的光子经历了整个宇宙的历史,宇宙演化的每一步都在它们的统计特性上留下了印记。对这些光子的观测有可能解开基础物理学和宇宙学的秘密,并为星系和星系团等宇宙结构的形成和演化提供关键见解。由于这些过程的痕迹是如此微弱,人们必须收集大量的数据集,才能在不可避免的仪器和环境噪音之上检测到它们。这反过来意味着必须能够使用最强大的计算资源来处理大量数据。这些计算资源包括高度本地化的超级计算机和广泛分布的网格和云系统。PI和Co-Is将开发一个能够利用这两种资源的通用计算基础设施,并通过调整四个领先的大爆炸天文台的分析管道来证明其适用于正在进行和计划中的实验。除了能够充分科学利用这些非常丰富的数据集,研究人员将指导从事这项研究的学生,并开办应用超级计算的暑期学校。该项目旨在探测宇宙微波背景辐射中最微弱的信号,特别是其偏振场的角功率谱中的峰和谷的图案。为了获得这些光谱,必须首先以保留信号中的相关性并表征噪声中的相关性的方式将原始观测结果简化为天空的地图。虽然执行这种简化的算法是很好理解的,但将它们应用于具有千万亿到千万亿观测值的数据集是一个非常严重的计算挑战。该项目可用于解决此问题的计算资源包括高性能和高吞吐量计算系统,并且需要利用它们两者。该项目将开发一个联合高性能/高通量计算框架,并在其中部署目前正在进行的阿塔卡玛宇宙学望远镜,BICEP/Keck阵列,POLARBEAR和南极望远镜实验的分析管道。通过这样做,人们也将证明计划中的西蒙斯天文台和CMB-S4实验的框架有效性。该项目由计算机信息科学工程局高级网络基础设施办公室&&和数学和物理科学局天文科学处支持。该奖项反映了NSF的法定使命,并通过使用基金会的评估被认为值得支持。知识价值和更广泛的影响审查标准。
项目成果
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