MRI: Acquisition of a High-Performance Computing Cluster to Unveil the Sources of Gravitational Waves

这笔赠款将允许购买高性能计算集群，这是西北大学研究人员调查引力波发射源所需的。随着科学家利用激光干涉仪引力波天文台的数据来探测黑洞和其他奇异天体(如中子星)，对引力波来源的建模和理解变得极其重要。在一个层面上，天文学家需要大型计算机来开发程序，帮助我们理解来自引力波探测器的大量数据，并从各种各样的噪声源中挑选出真正的天文学来源。但除此之外，随着对引力波源的探测越来越频繁，天文学家需要了解这些探测能告诉我们关于整个宇宙中奇异天体的数量。例如，考虑到已经探测到的引力波源，研究人员想知道在我们的星系和其他星系中可能有多少黑洞，它们的质量有多大？研究人员还问：这些黑洞是如何形成的，成对的黑洞系统是如何形成的？这些是理解已知物理定律极值天体的重要问题，要回答这些问题，天文学家不仅需要了解单个恒星的生命以及黑洞和中子星的形成，还需要模拟数百万恒星的群体，以及可能影响这些恒星发展的各种事件和过程。为了这项工作，天体物理学家需要大量非常高效的计算机，比如将用这些资金购买的计算机集群，以运行大规模模拟，帮助我们探索这些问题。除了将利用该集群进行的纯研究外，PI的团队还以生成他们的模拟的获奖可视化而闻名，这些可视化将用于各种科学、技术、工程和数学(STEM)教育和公共宣传活动。整个团队还在吸引不同的研究人员群体进入STEM研究和领域方面拥有丰富的经验；这个集群将帮助该群体在数据科学方法和科学计算方面培训新一代不同的研究人员，为国家的技术劳动力做出贡献。这笔赠款将允许获得一个高性能计算(HPC)集群，使其能够在新兴的引力物理领域进行研究。作为激光-干涉仪引力波观测站(LIGO)科学合作的一部分，引力波(GW)数据分析和GW源模拟用于探测的物理解释，该集群对于开发和优化所需代码至关重要。该设备包括一个具有InfiniBand网络的大型计算机集群(56个节点)和70 TB的可用存储。该集群将包含三个创新的图形编程单元节点(使用适合科学计算的GPU)，它们将用作特殊用途大规模并行计算的加速器。该集群将安装在西北大学校园内一流的HPC数据中心，并将由经验丰富的HPC专业团队运营和管理，团队由一名协理PI领导。更详细地说，该星系团将用于GW研究，重点是GW数据分析员(LIGO科学合作成员)、天体物理学家和计算机科学家之间的跨学科合作中具有两个致密天体(中子星和/或黑洞)的双星。我们的目标是优化对GW信号的数据搜索(通过有效的探测器表征)，尽可能迅速和准确地提取信号源的物理属性(通过不断改进我们的参数估计算法)，并推进对发现的天体物理解释，以便我们可以更好地了解GW信号的来源并利用我们的GW观测(通过在不同环境中开发最先进的形成模型并将预测与数据进行比较)来更好地了解信号源的来源和约束理论模型。该团队由Pi Kalogera和Pi Rasio共同领导，他们在这些研究领域的重大影响以及他们为GW数据分析和GW源天体物理建模创新开发的新计算工具而广为人知。

This grant will allow the purchase of a high-performance-computing cluster, which is required by researchers at Northwestern University to investigate sources of gravitational-wave emission. Modeling and understanding of gravitational-wave sources is becoming extremely important as scientists are utilizing data from the Laser Interferometer Gravitational-wave Observatory to detect black holes and other exotic astrophysical objects (such as "neutron stars"). On one level, astronomers require large computers to develop programs that can help us understand the large amounts of data from gravitational-wave detectors, and pick out the real, astronomical sources from a wide variety of noise sources. But in addition, as detections of gravitational-wave sources occur more frequently, astronomers need to understand what those detections can tell us about the population of exotic objects throughout the universe. For instance, given the detections of gravitational-wave sources already, researchers ask how many black holes there might be, in our galaxy, and in other galaxies, and how massive are they? Also, researchers ask: how do those black holes form, and how do systems of pairs of black holes form? These are important questions in understanding objects at the extreme of the known laws of physics, and to answer these questions, astronomers need to understand not only the lives of individual stars and the formation of black holes and neutron stars, but they need to simulate populations of millions of stars, and the wide variety of events and processes that can affect the development of those stars. For that work, astrophysicists require large collections of very efficient computers, such as the computer cluster that will be purchased with these funds, to run massive simulations that help us explore these questions. In addition to the pure research that will be done with this cluster, the PI's group is also well known for generating award-winning visualizations of their simulations, which will be used at a variety of Science, Technology, Engineering, and Mathematics (STEM) education and public-outreach events. The entire team also has extensive experience in attracting a diverse group of researchers to STEM research and fields; this cluster will help that group to train a new generation of diverse researchers in data-science methods and scientific computing, contributing to the technical workforce of the nation. This grant will allow the acquisition of a high-performance computing (HPC) cluster that will enable research in the emerging area of gravitational physics. The cluster will be essential to the development and optimization of codes needed for both gravitational-wave (GW) data analysis as part of the Laser-Interferometer Gravitational-wave Observatory (LIGO) Scientific Collaboration, and GW source modeling for the physical interpretation of the detections. The equipment consists of a large computer cluster (56 nodes) with InfiniBand networking and 70 TB of usable storage. This cluster will incorporate three innovative Graphics-Programming-Unit nodes (using GPUs appropriate for scientific computing) which will be used as accelerators for special-purpose massively parallel computations. The cluster will be housed at a top-of-the-line HPC data center on the Northwestern University campus and will be operated and managed by an experienced team of HPC professionals led by one of the co-PIs. In more detail, the cluster will be used for GW research focused on binaries with two compact objects (neutron stars and/or black holes) in interdisciplinary collaborations between GW data analysts (members of the LIGO Scientific Collaboration), astrophysicists, and computer scientists. The goals are to optimize data searches for GW signals (through effective detector characterization), to extract as promptly as possible and accurately the physical properties of the signal sources (through continuous improvements of our parameter-estimation algorithms), and to advance the astrophysical interpretation of the discoveries so we can better understand the sources' origin and constrain theoretical models using our GW observations (through the development of state-of-the-art formation models in different environments and comparing predictions to data). The team is led by PI Kalogera and co-PI Rasio, who are well recognized for their significant impact in these research areas and for their innovative development of new computational tools for GW data analysis and astrophysical modeling of GW sources.