Gravitational Wave Data Analysis: Inferring the Properties of Compact Objects and Searching for New Physics

该研究项目致力于引力波的分析和建模。当宇宙中的致密物体--如黑洞和中子星--绕轨道运行并碰撞时，空间和时间结构中的这些涟漪就会产生。由NSF资助的LIGO和欧洲Virgo合作项目对引力波的探测为宇宙打开了一扇新的窗口，揭示了以前看不见的事件，如成对的黑洞合并。该奖项支持的研究人员将作为LIGO合作的成员参与引力波的分析，帮助推断这些涟漪来源的性质。除了这些对天体物理学、宇宙学和核物理学具有深远影响的合作活动外，研究小组还将利用引力波数据进行新物理学的研究。引力波的探测提供了关于时空最动态的信息，允许强场相对论的测试，因为有可能探测到非常紧凑的物体，否则电磁观测是不可见的。这个奖项将使两个搜索引力波从新的，假设的紧凑型恒星，并使用最后的“振铃”合并黑洞搜索新的物理。这些研究活动将为研究生提供建模和数据分析方面的培训，这些技能对社会有很大的需求和很大的好处。此外，为了教育和启发公众对这一新的物理学和天文学领域的认识，小组成员还将开展外联活动。特别是，该项目的重点是通过引力波探测寻找新的物理学，同时继续支持LIGO科学合作组织，对该合作组织下一次观测活动中的探测结果进行贝叶斯参数估计。PI和小组的其他成员将参与参数估计管道的规划和开发，并对低延迟检测进行推断。这些推论是利用引力波了解致密天体的族群、从双星中子星的观测中推断核状态方程、检验相对论以及利用引力波测量宇宙膨胀的关键的第一步。该项目还将包括开发精确的降维波形模型，以便能够搜索具有大自旋诱导四极矩的低质量紧凑物体。目前的搜索可能会错过这些假设的物体，它们的探测将揭示奇异的新物理学。GstLAL搜索管道和随机模板库将用于在公开数据中搜索这些系统。该团队还将使用从量子力学微扰理论中借用的方法来预测相对论的可能偏差如何印在旋转黑洞的振铃光谱上。在预测特定偏差的频谱变化后，贝叶斯参数估计将用于约束或测量这些模型的基本参数，使用先前检测到的二元黑洞合并的振铃信号。该奖项反映了NSF的法定使命，并已被认为是值得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的支持。

This research project is devoted to the analysis and modeling of gravitational waves. These ripples in the very fabric of space and time are produced when the densest objects in the Universe -- such as black holes and neutron stars -- orbit and collide. The detection of gravitational waves by the NSF-funded LIGO and European Virgo collaborations has opened up a new window on the Universe, revealing previously invisible events like pairs of black holes merging. Researchers supported by this award will participate in the analysis of gravitational waves as members of the LIGO collaboration, helping to infer the properties of the sources of these ripples. In addition to these collaboration activities, which have far-reaching impacts on astrophysics, cosmology, and nuclear physics, the research group will carry out searches for new physics using gravitational-wave data. Detections of gravitational waves provide information about spacetime at its most dynamic, allowing for strong-field tests of relativity, as the possibility of detecting extremely compact objects which are otherwise invisible to electromagnetic observations. This award will enable both searches for gravitational waves from new, hypothetical compact stars, and use the final "ringdown" of merged black holes to search for new physics. These research activities will provide training for graduate students in modeling and data analysis, skillsets which are in great demand and of great benefit to society. In addition, members of the group will engage in outreach activities in order to educate and inspire the public about this new field of physics and astronomy.In particular, this project focuses on searching for new physics with gravitational wave detections, while continuing to support the LIGO Scientific Collaboration by performing Bayesian parameter estimation on detections made in the collaboration's next observing campaign. The PI and other members of the group will participate in the planning and development of parameter estimation pipelines, and carry out inferences on detections made in low latency. These inferences are a crucial first step in the use of gravitational waves for understanding the populations of compact objects, inferring the nuclear equation of state from observations of binary neutron stars, testing the theory of relativity, and using gravitational waves to measure cosmic expansion. The project will also include the development of accurate, reduced-dimensional waveform models to enable the search for low-mass compact objects with large spin-induced quadrupole moments. Such hypothetical objects can be missed by current searches, and their detection would reveal exotic new physics. The GstLAL search pipeline and random template banks will be used to carry out searches for these systems in publicly available data. The team will also use methods borrowed from quantum mechanical perturbation theory to predict how possible deviations from relativity are imprinted on the ringdown spectrum of spinning black holes. After predicting the changes to the spectrum from particular deviations, Bayesian parameter estimation will be used to constrain or measure the underlying parameters of these models using ringdown signals from previously detected binary black hole mergers.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.