Searches for Transient Gravitational Wave Signals

该奖项支持旨在扩大激光干涉仪引力波天文台(LIGO)探测各种瞬变源引力波信号的能力的研究，这些瞬变源包括黑洞合并和核心坍塌超新星。对瞬时引力波信号的增强搜索将采用强大的受限信号重建技术，该技术使用来自引力波探测器网络的数据。这种方法的一个关键要素是发展描述信号先验知识的约束。来自黑洞合并和核心坍塌超新星的数值模拟的信息将被用来构建特定于源的先验输入。一旦进行了检测，重要的是对信号进行表征，为描述信号的参数建立值。这将通过实施马尔可夫链蒙特卡罗采样例程来完成，以研究旋转的黑洞自旋信号和未建模的爆发信号。这些实现将被集成到标准LIGO搜索管道中，使用现有的基础设施来计算信号可能性。这些研究将与LIGO科学协作数据分析工作组密切合作进行。LIGO希望探测的大多数引力波信号都会在没有复杂的数据分析技术的情况下，隐藏在仪器噪声中而不被注意到。数据分析方面的增强可能与硬件升级一样有价值。LIGO项目为年轻的研究人员和学生提供了参与一门新的观测科学诞生的机会，该科学有望做出将彻底改变天文学的发现，并对宇宙中一些最奇异的现象提供独特的见解。该奖项支持的研究项目为研究生和本科生提供了学习这些具有潜在更广泛适用性的数据分析技术的机会。此外，一个关于引力波天文学的讲座项目正在开发中，将被带到蒙大拿州的学校。

This award supports research designed to extend the ability of the Laser Interferometer Gravitational-wave Observatory (LIGO) to detect gravitational wave signals from a variety of transient sources, including black hole mergers and core collapse supernovae. The enhanced searches for transient gravitational wave signals will employ the powerful technique of constrained signal reconstruction using data from a network of gravitational wave detectors. A key element of this approach is the development of constraints that describe prior knowledge of the signals. Information from numerical simulations of black hole mergers and core collapse supernovae will be used to construct source specific prior input. Once a detection has been made it is important that the signal be characterized values established for the parameters that describe the signal. This will be done through implementation of Markov Chain Monte Carlo sampling routines to study spinning black hole inspiral signals and un-modeled burst signals. These implementations will be integrated into the standard LIGO search pipelines using the existing infrastructure to compute signal likelihoods. These studies will be carried out in close collaboration with the LIGO Scientific Collaboration data analysis working groups. The majority of the gravitational wave signals that LIGO hopes to detect would pass by unnoticed, hidden in the instrument noise, without sophisticated data analysis techniques. Enhancements in data analysis can be just as valuable as hardware upgrades. The LIGO project presents young researchers and students with the opportunity to participate in the birth of a new observation science that is poised to make discoveries that will revolutionize astronomy and deliver unique insights into some of the Universe's most exotic phenomena. The research program supported by this award offers opportunities for graduate and undergraduate students to learn these data analysis techniques with potentially broader applicability. In addition, a lecture program on gravitational wave astronomy is being developed that will be taken to schools throughout Montana.