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Framework: An A+ Framework for Multimessenger Astrophysics Discoveries through Real-Time Gravitational Wave Detection

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
负责人:
Chad Hanna
金额:
$339.75万
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
项目状态:
未结题
起止时间:
2021-06-01 至 2026-05-31

项目摘要

项目成果

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中文摘要
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英文摘要
The first direct detection of ripples in space, known as gravitational waves, by the NSF-funded LIGO (Laser Interferometer Gravitational-wave Observatory) project in 2015 opened a new window on the universe and provided an unprecedented ability to study distant astronomical phenomena that could otherwise not be seen with conventional telescopes. The subsequent 2017 detection of merging neutron stars, through gravitational waves with LIGO combined with the light detected by conventional telescopes, opened a new era whereby scientists hope to routinely study the universe using information analogous to both sight and sound. This project will directly enable future detections of gravitational waves through the development of robust signal processing software and an ecosystem of cyberinfrastructure services designed to analyze LIGO data in real time. The program will involve a diverse group of undergraduate students, graduate students, postdoctoral researchers, computational scientists, and faculty in transformative science. This work contributes to the national cyberinfrastructure as a core data-producing component for astronomy and will be relied upon by thousands of scientists globally as they progress the state of knowledge through the study of black holes, neutron stars, fundamental physics, and the evolution of the Universe.With the goal of making new coincident gravitational-wave and electromagnetic observations commonplace, this project targets the development of a software framework for the real-time discovery of gravitational waves with the world-wide network of gravitational-wave detectors including LIGO, Virgo, and KAGRA. With this project, the investigators intend to provide a sustainable community-driven framework supporting current gravitational-wave detectors while developing new infrastructure for the LIGO A+ upgrade in about 2025. The team will develop a real-time gravitational wave processing framework around the following themes: 1) accelerating the pace of discovery and dissemination of results, 2) advancing the use of machine learning and artificial intelligence in production gravitational-wave astronomy, 3) improving scientific robustness and reproducibility, and 4) increasing adoption of the developed software and services. The framework will be used to create libraries, applications and services for real-time calibrated strain data, real-time data quality information and a quick-response gravitational-wave search for merging neutron stars and black holes, all of which will culminate in daily gravitational-wave discoveries released publicly. This framework will contribute gravitational-wave discovery services operating in a high-availability mode with the goal of greater than 99% uptime. A host of scientific metrics will be developed into a real-time test infrastructure to ensure that gravitational-wave alerts are accurate and robust throughout software development and release cycles. This research will have a far-reaching impact on several scientific disciplines with new gravitational-wave and multi-messenger astrophysics discoveries and it will impact society through a gradual change in the shared knowledge about the universe. Beyond these general societal impacts, the project personnel intend to directly weave training and participation broadening activities into their research through 1) training and broadening participation in the research community via quarterly workshops, 2) providing professional development opportunities for the project personnel through training seminars, and 3) engaging and educating the next generation of scientists in the geographic community with a summer school for high school students.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Windows on the Universe NSF Big Idea program, the Physics at the Information Frontier (PIF) program in the Division of Physics (PHY), and the Division of Astronomical Sciences (AST).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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Improving LIGO calibration accuracy by using time-dependent filters to compensate for temporal variations
通过使用瞬态滤波器补偿时间变化来提高 LIGO 校准精度
DOI: 10.1088/1361-6382/acabf6
发表时间: 2023
期刊: Classical and Quantum Gravity
影响因子: 3.5
作者: [Wade, M, Viets, A D, Chmiel, T, Stover, M, Wade, L]
通讯作者: Wade, L
DOI: 10.1103/physrevd.107.023024
发表时间: 2022-08
期刊: Physical Review D
影响因子: 5
作者: [Leo Tsukada;S. Jaraba;D. Agarwal;E. Floden]
通讯作者: Leo Tsukada;S. Jaraba;D. Agarwal;E. Floden
DOI: 10.1103/physrevd.106.084033
发表时间: 2021-10
期刊: Physical Review D
影响因子: 5
作者: [C. Hanna;P. Joshi;R. Huxford;K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;Miguel Fernandez;H. Fong;P. Godwin;R. Magee;D. Meacher;C. Messick;S. Morisaki;D. Mukherjee;H. Ohta;A. Pace;S. Privitera;S. Sachdev;S. Sakon;Divya Singh;R. Tapia;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno;A. Viets;L. Wade;M. Wade;Jonathan Wang]
通讯作者: C. Hanna;P. Joshi;R. Huxford;K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;Miguel Fernandez;H. Fong;P. Godwin;R. Magee;D. Meacher;C. Messick;S. Morisaki;D. Mukherjee;H. Ohta;A. Pace;S. Privitera;S. Sachdev;S. Sakon;Divya Singh;R. Tapia;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno;A. Viets;L. Wade;M. Wade;Jonathan Wang
DOI: 10.3847/2041-8213/ac082e
发表时间: 2021-07-01
期刊: ASTROPHYSICAL JOURNAL LETTERS
影响因子: 7.9
作者: [Abbott, R., Abbott, T. D., Zweizig, J.]
通讯作者: Zweizig, J.
Discovering Neutron Stars and Black Holes with LIGO
CC* Compute: An Open Science Grid shared computing platform at Penn State
CC* Team: Research Innovation with Scientists and Engineers (RISE)
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