Gravitational Wave Data Analysis: Parameter Inference and Black Hole Ringdown

引力波数据分析：参数推断和黑洞衰荡

• 批准号: 2308833
• 负责人: Aaron Zimmerman
• 金额: $ 24万
• 依托单位: University of Texas at Austin
• 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=2308833&HistoricalAwards=false
• 关键词: Gravitational; Wave; Data; Analysis; Parameter

This research project is devoted to the analysis and modeling of gravitational waves. These ripples in the 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 study how the final "ringdown" of merged black holes can be used 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 supporting 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 application of parameter estimation pipelines, carrying out inferences on detections made in low latency and helping to plan and execute comprehensive parameter analysis on longer timescales. 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. This project will also involve the investigation of systematic errors in parameter estimation when using cutting edge models, which exhibit complicated parameter degeneracies. 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. These predictions can be used in the future with Bayesian parameter estimation to constrain or measure the underlying parameters of these models using ringdown signals from 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.

本研究项目致力于引力波的分析和模拟。当宇宙中密度最大的物体--如黑洞和中子星--绕轨道运行并碰撞时，时空结构中的这些涟漪就会产生。由NSF资助的LIGO和欧洲处女座合作探测到的引力波打开了一扇了解宇宙的新窗口，揭示了以前看不见的事件，如黑洞对合并。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特性。除了这些对天体物理、宇宙学和核物理产生深远影响的合作活动外，研究小组还将利用引力波数据搜索新的物理。对引力波的探测提供了关于时空最动态的信息，允许对相对论进行强场测试，因为它有可能探测到电磁观测看不到的极其致密的物体。这一奖项将使人们能够从新的、假设的致密恒星中搜索引力波，并研究如何利用合并后的黑洞的最终“环化”来搜索新的物理。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，这些技能需求很大，对社会有很大的好处。此外，该小组的成员将开展外展活动，以教育和启发公众了解这一新的物理和天文学领域。特别是，该项目重点支持LIGO科学合作，对合作的下一次观测活动中的探测进行贝叶斯参数估计。PI和该小组的其他成员将参与参数估计管道的应用，对以低延迟进行的检测进行推断，并帮助规划和执行较长时间尺度的全面参数分析。这些推论是利用引力波了解致密天体的数量、从双中子星的观测推断核状态方程、测试相对论以及使用引力波测量宇宙膨胀的关键第一步。这个项目还将涉及使用尖端模型时参数估计中的系统误差的调查，这些模型表现出复杂的参数退化。该团队还将使用借用量子力学微扰理论的方法来预测可能的相对论偏差是如何印记在旋转黑洞的环形光谱上的。这些预测在未来可以与贝叶斯参数估计一起使用，使用来自二元黑洞合并的振铃信号来约束或测量这些模型的基本参数。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。