Gravitational-Wave Astronomy and Astrophysics at Syracuse University

雪城大学引力波天文学和天体物理学

• 批准号: 2309240
• 负责人: Alexander Nitz
• 金额: $ 18万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309240&HistoricalAwards=false
• 关键词: Gravitational; Wave; Astronomy; Astrophysics; Syracuse

Gravitational-wave astronomy has given humanity a completely new way to observe the universe. The National Science Foundation’s Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) now routinely detects astrophysical sources of gravitational waves. Science now has an observatory that will allow us to peer into the cores of exploding stars, probe the interiors of neutron stars, and explore the extreme physics of colliding black holes. The discovery of the binary neutron star merger GW170817 was accompanied by light across the electromagnetic spectrum and inaugurated the use of gravity as an instrument of multi-messenger astronomy. The dramatic breakthroughs made by LIGO and Virgo are only the beginning of our exploration of the gravitational-wave sky. Advanced LIGO is joined by Advanced Virgo, KAGRA, and eventually there will be the next-generation observatories, Cosmic Explorer and Einstein Telescope. New algorithms are required to achieve the full scientific potential of the growing global observatory network. This award will support the development of new gravitational-wave search algorithms that will lay the foundation for the next generation and open a window to the discovery of new classes of merging binaries. Developing these algorithms will also equip students with the skills needed to enhance the competitiveness of the U.S. STEM workforce.This research investigates multi-detector coherent search algorithms that take advantage of Bayesian tools developed for gravitational-wave astronomy. The optimal approach to detect gravitational-wave sources is a fully Bayesian analysis that can coherently combine gravitational-wave data from multiple detectors and accurately model both gravitational-wave signals and detector noise which may contain non-Gaussian transient noise, aka ’glitches’. Currently employed searches employ heuristics that approximate the optimal approach and enable them to be tractable on available computing resources. While this has been an effective strategy for the early era of gravitational-wave astronomy, these approaches sacrifice sensitivity and flexibility. Algorithms will be explored that enable efficient hierarchical analysis of gravitational-wave data and rapid Bayesian evidence estimation. This approach reduces the barriers between searching for sources and the estimation of source parameters, enabling the reuse of research in either regime into the modeling of glitches, detector nonstationarity, and overlapping signals.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.

引力波天文学为人类提供了一种全新的观察宇宙的方式。国家科学基金会的高级激光干涉仪重力波天文台（LIGO）现在常规地检测出引力波的天体物理来源。现在，科学的观察结果将使我们能够凝视着爆炸恒星的核心，探测中子恒星的内部，并探索碰撞黑洞的极端物理。二进制中子星合并GW170817的发现伴随着电子光谱的光，并启动了将重力作为多门徒天文学的仪器的使用。 Ligo和处女座创造的戏剧性突破只是我们探索引力波天空的开始。 Advanced Ligo与高级处女座，Kagra一起加入，最终将有下一代观察者，Cosmic Explorer和Einstein望远镜。需要新的算法来实现不断增长的全球观察网络的全部科学潜力。该奖项将支持开发新的重力波搜索算法，该算法将为下一代奠定基础，并为发现新类合并二进制文件打开一个窗口。开发这些算法还将为学生提供提高美国STEM劳动力竞争力所需的技能。这项研究研究了多探测器相干搜索算法，这些搜索算法利用了为重力波天文学开发的贝叶斯工具。检测重力波源的最佳方法是一种完全贝叶斯分析，可以连贯地结合来自多个检测器的重力波数据，并准确地对引力波信号和检测器噪声进行准确模拟，该噪声可能包含非高斯瞬态噪声，即aka'aka'glitches’。目前采用的搜索采用了近似最佳方法的启发式方法，并使它们能够在可用的计算资源上进行处理。尽管这是重力波天文学早期时代的有效策略，但这些方法牺牲了敏感性和灵活性。将探索算法，即对重力波数据和快速贝叶斯证据估计进行有效的分层分析。这种方法减少了寻找来源和源参数估算之间的障碍，使在制度中的研究重复使用到小故障，探测器非机构性和重叠信号之间的障碍。该奖项反映了NSF的法规使命，并认为通过基金会的知识绩效和广泛的crietia crietia criperia criperia criperia criperia the Issportion the Pocie take criped supportiation。