Scalable Cyberinfrastructure for Early Warning Gravitational Wave Detections
用于早期预警引力波探测的可扩展网络基础设施
基本信息
- 批准号:1841480
- 负责人:
- 金额:$ 98.39万
- 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:2018-10-01 至 2021-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Recent advances in astronomical facilities have opened new windows on the universe that extend observing capabilities beyond conventional telescopes. Joint observations that combine telescopes, neutrino detectors, and new gravitational wave detectors including the NSF-supported LIGO Observatory are revealing aspects of the universe that are presently a mystery. Just recently, signals from the collision of two extremely dense neutron stars - a merger known as GW170817 - were detected by both conventional telescopes and gravitational wave detectors. The event was detected first in gravitational waves, two seconds later in gamma rays, after 10 hours in optical, ultraviolet, infrared, and much later in x-ray and radio waves. From this single event, the world learned that some short-hard gamma ray bursts indicate neutron star mergers, that these mergers might be the origin of many elements in the periodic table such as gold and platinum, that gravity and light travel at the same speed, and that gravitational waves really could measure how fast the universe is expanding. Despite what was learned, GW170817 left the world with many questions. What object was formed afterward? Was it another neutron star? Was it a black hole? Why was the gamma ray burst associated with GW170817 unlike anything else that had been observed? Answering these questions, and conducting these kinds of joint observations on a regular basis, requires significant computing and software infrastructure (cyberinfrastructure).The project proposes to develop the cyberinfrastructure necessary to give earlier gravitational event alerts to other astronomical facilities than is currently possible, allowing researchers to collect as much data as possible about these new types of celestial events. This project will fortify the streaming data delivery of LIGO by producing sub-second data delivery to a streaming early warning search for neutron star mergers. Substantial automated monitoring and feedback will ensure the entire system operates without manual intervention. The project will capitalize upon existing NSF investments in cyber-infrastructure for real-time gravitational wave analysis and will significantly augment the data delivery and automation layer for detections which is presently a bottleneck and failure mode. Using gravitational waves to provide an early warning for robotic telescopes will significantly enhance the scientific utility of LIGO data and significantly facilitate multi-messenger astrophysics. This proposal will promote the progress of science in two of the National Science Foundation's 10 Big Ideas: "Harnessing the Data Revolution" "Windows on the Universe: The Era of Multi-Messenger Astrophysics". This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering.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.
天文学设施的最新进展打开了观察宇宙的新窗口,使观测能力超越了传统望远镜。联合观测结合了联合收割机望远镜,中微子探测器和新的引力波探测器,包括NSF支持的LIGO天文台,正在揭示宇宙的各个方面,目前是一个谜。就在最近,传统望远镜和引力波探测器都探测到了两颗密度极高的中子星相撞的信号,这颗中子星被称为GW 170817。 这一事件首先在引力波中被发现,两秒钟后在伽马射线中被发现,10小时后在光学,紫外线,红外线中被发现,更晚的时候在X射线和无线电波中被发现。 从这一事件中,世界了解到一些短硬伽马射线爆发表明中子星星合并,这些合并可能是周期表中许多元素的起源,如金和铂,引力和光以相同的速度传播,引力波确实可以测量宇宙膨胀的速度。 尽管有了这些知识,GW170817还是给世界留下了许多问题。后来形成了什么东西?是另一颗中子星星吗?是黑洞吗?为什么与GW170817相关的伽马射线暴与其他观测到的不同?解决这些问题并定期进行此类联合观测需要大量的计算和软件基础设施(网络基础设施)。该项目建议开发必要的网络基础设施,以便比目前更早地向其他天文设施发出引力事件警报,使研究人员能够收集尽可能多的关于这些新型天体事件的数据。该项目将通过为中子星星合并的流早期预警搜索提供亚秒级数据传输来加强LIGO的流数据传输。大量的自动化监控和反馈将确保整个系统在没有人工干预的情况下运行。该项目将利用NSF在网络基础设施方面的现有投资进行实时引力波分析,并将显著增强数据传输和自动化检测层,这是目前的瓶颈和故障模式。利用引力波为机器人望远镜提供早期预警将大大提高LIGO数据的科学效用,并大大促进多信使天体物理学。 该提案将促进美国国家科学基金会10大理念中的两个理念的科学进步:“利用数据革命”“宇宙之窗:多信使天体物理学时代”。该项目得到了计算机和信息科学与工程局高级网络基础设施办公室的支持。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Early warning of coalescing neutron-star and neutron-star-black-hole binaries from the nonstationary noise background using neural networks
- DOI:10.1103/physrevd.104.062004
- 发表时间:2021-04
- 期刊:
- 影响因子:5
- 作者:Hang Yu;R. Adhikari;R. Magee;S. Sachdev;Yanbei Chen
- 通讯作者:Hang Yu;R. Adhikari;R. Magee;S. Sachdev;Yanbei Chen
First Demonstration of Early Warning Gravitational-wave Alerts
- DOI:10.3847/2041-8213/abed54
- 发表时间:2021-04-01
- 期刊:
- 影响因子:7.9
- 作者:Magee, Ryan;Chatterjee, Deep;Zweizig, John
- 通讯作者:Zweizig, John
Fast evaluation of multidetector consistency for real-time gravitational wave searches
- DOI:10.1103/physrevd.101.022003
- 发表时间:2019-01
- 期刊:
- 影响因子:5
- 作者:C. Hanna;S. Caudill;C. Messick;A. Reza;S. Sachdev;L. Tsukada;K. Cannon;K. Blackburn;J. Creighton;H. Fong;P. Godwin;S. Kapadia;T. Li;R. Magee;D. Meacher;D. Mukherjee;A. Pace;S. Privitera;R. K. Lo;L. Wade
- 通讯作者:C. Hanna;S. Caudill;C. Messick;A. Reza;S. Sachdev;L. Tsukada;K. Cannon;K. Blackburn;J. Creighton;H. Fong;P. Godwin;S. Kapadia;T. Li;R. Magee;D. Meacher;D. Mukherjee;A. Pace;S. Privitera;R. K. Lo;L. Wade
An Early-warning System for Electromagnetic Follow-up of Gravitational-wave Events
- DOI:10.3847/2041-8213/abc753
- 发表时间:2020-08
- 期刊:
- 影响因子:0
- 作者:S. Sachdev;R. Magee;C. Hanna;K. Cannon;L. Singer;J. Sk;D. Mukherjee;S. Caudill;C. Chan;J. Creighton;B. Ewing;H. Fong;P. Godwin;R. Huxford;S. Kapadia;A. Li;Rico Ka Lok Lo;D. Meacher;C. Messick;S. Mohite;A. Nishizawa;H. Ohta;A. Pace;A. Reza;B. Sathyaprakash;M. Shikauchi;Divya Singh;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno
- 通讯作者:S. Sachdev;R. Magee;C. Hanna;K. Cannon;L. Singer;J. Sk;D. Mukherjee;S. Caudill;C. Chan;J. Creighton;B. Ewing;H. Fong;P. Godwin;R. Huxford;S. Kapadia;A. Li;Rico Ka Lok Lo;D. Meacher;C. Messick;S. Mohite;A. Nishizawa;H. Ohta;A. Pace;A. Reza;B. Sathyaprakash;M. Shikauchi;Divya Singh;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno
GstLAL: A software framework for gravitational wave discovery
- DOI:10.1016/j.softx.2021.100680
- 发表时间:2020-10
- 期刊:
- 影响因子:3.4
- 作者:K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;H. Fong;P. Godwin;C. Hanna
- 通讯作者:K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;H. Fong;P. Godwin;C. Hanna
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Chad Hanna其他文献
Searching for asymmetric and heavily precessing Binary Black Holes in the gravitational wave data from the LIGO and Virgo third Observing Run
在 LIGO 和 Virgo 第三次观测运行的引力波数据中寻找不对称和严重进动的双黑洞
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Stefano Schmidt;S. Caudill;J. Creighton;L. Tsukada;Anarya Ray;S. Adhicary;Pratyusava Baral;A. Baylor;Kipp Cannon;B. Cousins;B. Ewing;Heather Fong;Richard N. George;P. Godwin;Chad Hanna;Reiko Harada;Yun;R. Huxford;Prathamesh Joshi;J. Kennington;Soichiro Kuwahara;A. K. Li;R. Magee;D. Meacher;C. Messick;S. Morisaki;D. Mukherjee;Wanting Niu;A. Pace;C. Posnansky;S. Sachdev;S. Sakon;Divya R. Singh;Urja Shah;R. Tapia;T. Tsutsui;K. Ueno;A. Viets;L. Wade;M. Wade - 通讯作者:
M. Wade
Searching for gravitational waves from compact binary coalescence
- DOI:
- 发表时间:
2011-04 - 期刊:
- 影响因子:0
- 作者:
Chad Hanna - 通讯作者:
Chad Hanna
Chad Hanna的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Chad Hanna', 18)}}的其他基金
CC* Data Storage: Cost-effective Attached Storage for High throughput computing using Homo- geneous IT (CASH HIT) supporting Penn State Science, the Open Science Grid and LIGO
CC* 数据存储:使用同质 IT (CASH HIT) 实现高吞吐量计算的经济高效附加存储,支持宾夕法尼亚州立大学科学学院、开放科学网格和 LIGO
- 批准号:
2346596 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Discovering Neutron Stars and Black Holes with LIGO
利用 LIGO 发现中子星和黑洞
- 批准号:
2308881 - 财政年份:2023
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
CC* Compute: An Open Science Grid shared computing platform at Penn State
CC* 计算:宾夕法尼亚州立大学的开放科学网格共享计算平台
- 批准号:
2201445 - 财政年份:2022
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Framework: An A+ Framework for Multimessenger Astrophysics Discoveries through Real-Time Gravitational Wave Detection
框架:通过实时引力波探测进行多信使天体物理学发现的框架
- 批准号:
2103662 - 财政年份:2021
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
CC* Team: Research Innovation with Scientists and Engineers (RISE)
CC* 团队:科学家和工程师的研究创新 (RISE)
- 批准号:
2018299 - 财政年份:2020
- 资助金额:
$ 98.39万 - 项目类别:
Continuing Grant
Discovering Black Holes and Neutron Stars with LIGO
利用 LIGO 发现黑洞和中子星
- 批准号:
2011865 - 财政年份:2020
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
SI2-SSE: Hearing the Signal through the Static: Realtime Noise Reduction in the Hunt for Binary Black Holes and other Gravitational Wave Transients
SI2-SSE:通过静电听到信号:寻找双黑洞和其他引力波瞬变过程中的实时降噪
- 批准号:
1642391 - 财政年份:2016
- 资助金额:
$ 98.39万 - 项目类别:
Continuing Grant
CAREER: Enabling Multimessenger Astrophysics with Real-Time Gravitational Wave Detection
职业:通过实时引力波检测实现多信使天体物理学
- 批准号:
1454389 - 财政年份:2015
- 资助金额:
$ 98.39万 - 项目类别:
Continuing Grant
相似海外基金
CC* Campus Compute: UTEP Cyberinfrastructure for Scientific and Machine Learning Applications
CC* 校园计算:用于科学和机器学习应用的 UTEP 网络基础设施
- 批准号:
2346717 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
CC* Planning: Strengthening Central Michigan University's Cyberinfrastructure
CC* 规划:加强中央密歇根大学的网络基础设施
- 批准号:
2345749 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
- 批准号:
2403312 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
CC* Networking Infrastructure: Building a Scalable and Polymorphic Cyberinfrastructure for Diverse Research and Education Needs at Illinois State University
CC* 网络基础设施:为伊利诺伊州立大学的多样化研究和教育需求构建可扩展和多态的网络基础设施
- 批准号:
2346712 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Travel: Support for U.S. Students to Receive Training on Research Cyberinfrastructure at the 2024 Annual Modeling and Simulation Conference (ANNSIM)
旅行:支持美国学生在 2024 年年度建模与仿真会议 (ANNSIM) 上接受研究网络基础设施培训
- 批准号:
2425778 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
CICI: TCR: Transitioning Differentially Private Federated Learning to Enable Collaborative, Intelligent, Fair Skin Disease Diagnostics on Medical Imaging Cyberinfrastructure
CICI:TCR:转变差异化私有联合学习,以实现医学影像网络基础设施上的协作、智能、公平的皮肤病诊断
- 批准号:
2319742 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Data-enabled Pathways to Equity in Cyberinfrastructure Utilization for Scientific Discovery
利用数据实现科学发现的网络基础设施公平之路
- 批准号:
2346631 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Conference: Cyberinfrastructure Leadership Academy: Team Science and Grand Challenges
会议:网络基础设施领导学院:团队科学和重大挑战
- 批准号:
2414440 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
- 批准号:
2403313 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant
Collaborative Research: CyberTraining: Implementation: Small: Inclusive Cyberinfrastructure and Machine Learning Training to Advance Water Science Research
合作研究:网络培训:实施:小型:包容性网络基础设施和机器学习培训,以推进水科学研究
- 批准号:
2320980 - 财政年份:2024
- 资助金额:
$ 98.39万 - 项目类别:
Standard Grant














{{item.name}}会员




