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

从2015年首次直接探测到引力波开始，NSF的LIGO天文台已经产生了杰出的科学发现。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。迄今为止最令人兴奋的发现之一是GW170817，它是由两颗中子星合并产生的，随后是伽马射线爆发，伴随着独特的x射线、可见光、红外线和射电辐射，这些辐射贯穿了天文学家使用的整个电磁波谱。那次“多信使”事件揭示了伽玛射线爆发的天体物理学、超致密中子星的物理特性、引力波相对于光的速度，以及金等重元素的来源等新信息——这是美国国家科学基金会“宇宙之窗”倡议的一个显著成功。先进的LIGO探测器，以及欧洲的Virgo探测器和日本的KAGRA探测器，目前正在为他们的第四次观测运行做准备。该奖项支持改进数据分析方法的研究，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措施，从而更好地研究使用引力波的天体物理学和基础物理学。该奖项还支持实时数据分析操作和快速检查，以便可靠的候选事件可以快速传达给天文学家，从而实现快速后续观测，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，以及与公众分享LIGO科学成果和一般科学概念的推广活动。该奖项支持的研究将在两个主要领域推进NSF的LIGO和该项目的国际合作伙伴的科学计划：在即将到来的O4观测运行中改进对紧凑双星聚结（CBC）事件的检测，并确保准备好检测和研究下一个伟大的多信使事件-或者接下来的几个，正如大自然所提供的那样。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生产分析，为下一个LIGO-Virgo-KAGRA （LVK）瞬态事件目录提供信息，进一步推进LVK合作目标，同时培养研究生研究人员的科学技能和经验。该合同还将支持其他数据分析管道的验证和监控，以及LVK科学家在发现有希望的候选人时协调快速反应活动的工具和程序。该合同还将支持合作工具的维护，以计划、跟踪、发布和传播LVK从O4观测运行中获得的科学结果。最后，它将为马里兰大学物理系的年轻学生STEM教育/拓展项目提供一些资金。该奖项反映了美国国家科学基金会的法定使命，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。

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.