WoU-MMA: Gravitational Wave Data Analysis and Tools for Multi-Messenger Astrophysics

WoU-MMA：多信使天体物理学的引力波数据分析和工具

• 批准号: 2309085
• 负责人: Peter Shawhan
• 金额: $ 10万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309085&HistoricalAwards=false
• 关键词: WoU; MMA; Gravitational; Wave; Data

NSF’s LIGO observatories have produced outstanding scientific discoveries, beginning with the first direct detection of gravitational waves in 2015. To date, over 90 gravitational-wave signals have been detected by the LIGO Scientific Collaboration together with its international partners. One of the most exciting discoveries so far was the event named GW170817, which was produced when two neutron stars merged and was followed by a gamma-ray burst along with distinctive X-ray, visible-light, infrared, and radio emissions across the whole electromagnetic spectrum used by astronomers. That “multi-messenger” event revealed new information about the astrophysics of gamma-ray bursts, the physical properties of super-dense neutron stars, the speed of gravitational waves versus light, and the source of heavy elements like gold – a remarkable success of NSF’s “Windows on the Universe” initiative. The Advanced LIGO detectors, along with the European Virgo detector and Japanese KAGRA detector, are currently being prepared for their fourth observing run. This award is supporting research to improve the data analysis methods in order to increase the number of gravitational-wave signals that can be identified in the data, by using machine learning techniques to make use of measures of data quality, to enable even better studies of astrophysics and fundamental physics using gravitational waves. This award also supports real-time data analysis operations and rapid checks so that reliable candidate events can quickly be communicated to astronomers, to enable rapid follow-up observations leading to the next multi-messenger breakthroughs. The award supports the training of a graduate-student scientist and outreach activities to share LIGO science results and general science concepts with the public.The research supported by this award will advance the science program of NSF's LIGO and the project's international partners in two main areas: improving the detection of compact binary coalescence (CBC) events in the upcoming O4 observing run, and ensuring readiness to detect and study the next great multi-messenger event – or the next few, as nature provides. The PyCBC data analysis pipeline will be improved by incorporating data quality information into the detection statistic using machine learning methods, an approach which has been demonstrated (in preliminary studies) to improve the net sensitivity of searches. The upgraded PyCBC pipeline will be used both for low-latency searches and for the final production analysis feeding into the next LIGO-Virgo-KAGRA (LVK) transient event catalog, furthering LVK collaboration goals while developing the scientific skills and experience of a graduate student researcher. This award will also support the validation and monitoring of other data analysis pipelines, and tools and procedures to coordinate rapid response activities by LVK scientists when a promising candidate has been found. This award also will support the maintenance of collaboration tools to plan, track, publish and disseminate the LVK’s science results from the O4 observing run. Finally, it will provide some funds for supplies for the University of Maryland Physics Department’s STEM education/outreach programming for young students.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.

NSF的LIGO天文台已经产生了杰出的科学发现，从2015年首次直接探测到引力波开始。 迄今为止，LIGO科学合作组织及其国际合作伙伴已经探测到90多个引力波信号。 到目前为止，最令人兴奋的发现之一是名为GW 170817的事件，它是由两颗中子星合并产生的，随后是伽马射线爆发，沿着独特的X射线，可见光，红外线和无线电发射，横跨天文学家使用的整个电磁频谱。 这一“多信使”事件揭示了有关伽马射线爆发的天体物理学、超密度中子星的物理性质、引力波相对于光速的速度以及金等重元素的来源的新信息--这是美国国家科学基金会“宇宙之窗”计划的一个显著成功。 先进的LIGO探测器，沿着欧洲的Virgo探测器和日本的KAGRA探测器，目前正在准备进行第四次观测。 该奖项支持研究改进数据分析方法，以增加可以在数据中识别的引力波信号的数量，通过使用机器学习技术来利用数据质量的测量，从而使用引力波更好地研究天体物理和基础物理。 该奖项还支持实时数据分析操作和快速检查，以便将可靠的候选事件快速传达给天文学家，从而实现快速跟踪观测，从而实现下一个多信使突破。 该奖项支持培养一名研究生科学家，并开展外联活动，与公众分享LIGO科学成果和一般科学概念。该奖项支持的研究将在两个主要领域推进NSF LIGO和该项目国际合作伙伴的科学计划：在即将到来的O 4观测运行中改进对致密双星合并（CBC）事件的探测，并确保准备好检测和研究下一个伟大的多信使事件-或未来几个，因为自然提供。 PyCBC数据分析管道将通过使用机器学习方法将数据质量信息纳入检测统计来改进，这种方法已被证明（在初步研究中）可以提高搜索的净灵敏度。 升级后的PyCBC管道将用于低延迟搜索和最终的生产分析，以输入下一个LIGO-Virgo-KAGRA（LVK）瞬态事件目录，进一步实现LVK合作目标，同时培养研究生研究人员的科学技能和经验。 该奖项还将支持其他数据分析管道的验证和监测，以及在发现有前途的候选人时协调LVK科学家快速响应活动的工具和程序。该奖项还将支持维护合作工具，以计划，跟踪，发布和传播LVK从O 4观测运行中获得的科学成果。 最后，它将为马里兰州大学物理系的STEM教育/青年学生外展计划提供一些资金。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。