MRI: Acquisition of a Computing Cluster for Gravitational-Wave and Multimessenger Astrophysics in the Era of LIGO Detections

MRI：在 LIGO 探测时代获取用于引力波和多信使天体物理的计算集群

• 批准号: 1726215
• 负责人: Manuela Campanelli
• 金额: $ 34.67万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1726215&HistoricalAwards=false
• 关键词: MRI; Acquisition; Computing; Cluster; Gravitational

This MRI award supports a team of researchers at the Rochester Institute of Technology's (RIT) Center for Computational Relativity and Gravitation (CCRG) to acquire, deploy, and maintain a new state-of-the art computational cluster, GreenPrairie, to be used in research at the frontiers of gravitational physics, relativistic astrophysics, advanced high-performance computation, and scientific visualization. GreenPrairie will be the main computational workhorse of the CCRG, and it will directly enable the research of undergraduate and graduate students, postdoctoral researchers, and faculty across four departments and three colleges at RIT. It will foster the growth of three graduate programs in astrophysics, mathematical modeling, and computer science, and support research on behalf of several large community-wide collaborations in numerical relativity, gravitational waveform source modeling, and relativistic astrophysics. Scientific visualizations from the cluster will be used to support a funded REU program on multi-messenger astrophysics, and programs at RIT's National Technical Institute for the Deaf to promote science to the deaf and hard-of-hearing communities. The cluster will also be a vehicle for public outreach events on science, mathematics, and computing through site visits and annual community-wide public exhibits.GreenPrairie consists of a 1296-core, high-speed, large-memory computer cluster, with 768 TB of attached storage, and will be housed within the "Black Hole Lab" computer facility at the CCRG. Research with GreenPrairie will focus on some of the most extreme phenomena in the universe, where the strongest gravitational and magnetic fields interact with ultra-relativistic matter and high-energy radiation, that can only be studied through advanced, large-scale computation and visualization. The cluster will be used for timely simulations of key astrophysical sources for advanced LIGO, which uses information from theoretical waveforms to interpret the observed signals and determine the nature of the astrophysical sources. Specifically, the cluster will be used to simulate black-hole binaries, and their merger waveforms, across the entire space of parameters relevant to advanced LIGO and next generation detectors, as well as fast response simulations triggered by gravitational wave detections. The cluster will also be used to study accretion problems involving close and/or merging binary black hole systems which are expected to be observable in the electromagnetic spectrum by current and future astronomical surveys, such as LSST. Finally, the cluster will be a testbed for developing novel computational techniques that will permit efficient computation of heterogeneous systems involving multiple kinds of physics with very different length scales, and multiple evolution schemes.

该 MRI 奖项支持罗切斯特理工学院 (RIT) 计算相对论和引力中心 (CCRG) 的研究团队获取、部署和维护一个新的最先进的计算集群 GreenPrairie，用于引力物理学、相对论天体物理学、先进高性能计算和科学可视化的前沿研究。 GreenPrairie 将成为 CCRG 的主要计算主力，它将直接支持 RIT 四个系和三个学院的本科生和研究生、博士后研究人员和教师的研究。它将促进天体物理学、数学建模和计算机科学三个研究生项目的发展，并支持代表数值相对论、引力波形源建模和相对论天体物理学方面的几个大型全社区合作的研究。该集群的科学可视化将用于支持 REU 资助的多信使天体物理学项目，以及 RIT 国家聋人技术研究所向聋人和听力障碍群体推广科学的项目。 该集群还将通过现场参观和年度社区范围内的公共展览，成为科学、数学和计算方面公共宣传活动的载体。GreenPrairie 由一个 1296 核、高速、大内存计算机集群组成，容量为 768 TB附加存储，并将安置在 CCRG 的“黑洞实验室”计算机设施内。 GreenPrairie 的研究将集中于宇宙中一些最极端的现象，其中最强的引力场和磁场与超相对论物质和高能辐射相互作用，这些现象只能通过先进的大规模计算和可视化来研究。该集群将用于及时模拟先进 LIGO 的关键天体物理源，LIGO 使用理论波形信息来解释观测到的信号并确定天体物理源的性质。具体来说，该集群将用于模拟黑洞双星及其合并波形，涵盖与先进 LIGO 和下一代探测器相关的整个参数空间，以及由引力波检测触发的快速响应模拟。该星团还将用于研究涉及近距离和/或合并双黑洞系统的吸积问题，这些系统预计可以通过当前和未来的天文观测（例如 LSST）在电磁频谱中观测到。最后，该集群将成为开发新颖计算技术的测试平台，该技术将允许对涉及长度尺度差异很大的多种物理和多种演化方案的异构系统进行有效计算。

项目成果

Quasi-periodicity of Supermassive Binary Black Hole Accretion Approaching Merger

超大质量双黑洞吸积接近合并的准周期性

• DOI: 10.3847/1538-4357/ab2453
• 发表时间: 2019-07
• 期刊: The Astrophysical Journal
• 作者: Bowen, Dennis B.;Mewes, Vassilios;Noble, Scott C.;Avara, Mark;Campanelli, Manuela;Krolik, Julian H.
• 通讯作者: Krolik, Julian H.

Hangup effect in unequal mass binary black hole mergers and further studies of their gravitational radiation and remnant properties

不等质量双黑洞并合中的挂断效应及其引力辐射和残余特性的进一步研究

• DOI: 10.1103/physrevd.97.084002
• 发表时间: 2018-04
• 期刊: Physical Review D
• 影响因子: 5
• 作者: Healy, James;Lousto, Carlos O.
• 通讯作者: Lousto, Carlos O.

A Fermi Gamma-Ray Burst Monitor Search for Electromagnetic Signals Coincident with Gravitational-wave Candidates in Advanced LIGO's First Observing Run

费米伽马射线爆发监视器搜索与先进 LIGO 首次观测运行中的引力波候选信号一致的电磁信号

• DOI: 10.3847/1538-4357/aaf726
• 发表时间: 2019-01
• 期刊: The Astrophysical Journal
• 作者: Burns, E.;Goldstein, A.;Hui, C. M.;Blackburn, L.;Briggs, M. S.;Connaughton, V.;Hamburg, R.;Kocevski, D.;Veres, P.;Wilson;et al
• 通讯作者: et al

Electromagnetic Signatures from Supermassive Binary Black Holes Approaching Merger

即将合并的超大质量双黑洞的电磁特征

• DOI: 10.3847/1538-4357/ac56de
• 发表时间: 2022-04
• 期刊: The Astrophysical Journal
• 作者: Gutiérrez, Eduardo M.;Combi, Luciano;Noble, Scott C.;Campanelli, Manuela;Krolik, Julian H.;López Armengol, Federico;García, Federico
• 通讯作者: García, Federico

All-sky search for short gravitational-wave bursts in the third Advanced LIGO and Advanced Virgo run

在第三次 Advanced LIGO 和 Advanced Virgo 运行中对短引力波爆发进行全天搜索

• DOI: 10.1103/physrevd.104.122004
• 发表时间: 2021-12
• 期刊: Physical Review D
• 影响因子: 5
• 作者: Abbott, R.;Abbott, T. D.;Acernese, F.;Ackley, K.;Adams, C.;Adhikari, N.;Adhikari, R. X.;Adya, V. B.;Affeldt, C.;Agarwal, D.;et al
• 通讯作者: et al