Gravitational Wave Models for Black Hole - Neutron Stars in General Relativity and Beyond

该奖项支持相对论和相对论天体物理学的研究，并解决了NSF“宇宙之窗”大理念的优先领域。2015年获得诺贝尔奖的LIGO探测器对双黑洞合并产生的引力波的观测揭示了一个全新的宇宙窗口。随后是对双中子星星和黑洞-中子星星合并的开创性观测。引力波天文学的一个关键目标是在这些合并的极端条件下测试爱因斯坦的广义相对论，在这些条件下，量子引力效应等新物理学可能变得重要。该项目的主要目标是开发新的数值模拟和数据驱动模型，这些模型对进行这些测试至关重要，并有助于最大限度地发挥引力波观测的科学影响。该项目包括对学生的支持以及当地学校和观察站的外联部分，从而直接促进新兴STEM领域的导师制，招聘和保留。学生们获得的计算技能适用于更广泛的领域，如数据科学和机器学习，为他们在学术界和工业界的广泛成功职业生涯做好准备。该奖项是关于在广义相对论和替代理论中预测黑洞-中子星星和双中子星星合并的引力波信号的数值模拟和模型的发展。随着我们的引力波探测器不断改进，有必要改进我们的引力波模型，用于与观测数据进行比较，并在强场区域测试广义相对论。这项研究通过在广义相对论以及标量张量引力等替代理论中对黑洞-中子星星和双中子星星合并进行新的数值模拟来解决这一迫切需要。其次是构建数据驱动的代理模型，准确地再现模拟中的引力波信号。此类模拟和模型对于可靠地提取天体物理源属性并使用这些观测来测试广义相对论至关重要。该奖项反映了NSF的法定使命，并且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。

This award supports research in relativity and relativistic astrophysics, and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. The 2015 Nobel prize-winning observation of gravitational waves from a binary black hole merger by the LIGO detectors unveiled an entirely new window to the universe. This was followed up by the groundbreaking observations of binary neutron star and black hole-neutron star mergers. One of the key goals of gravitational wave astronomy is to test Einstein’s general relativity under the extreme conditions of these mergers, where new physics like quantum gravity effects can become important. The main objective of this project is to develop novel numerical simulations and data-driven models that are critical for conducting these tests and help maximize the scientific impact of gravitational wave observations. This project includes support for students as well as outreach components at local schools and observatories, thereby contributing directly to mentorship, recruitment, and retention in an emerging STEM area. The computational skills gained by the students are applicable in broader areas like data science and machine learning, preparing them for a wide range of successful careers in academia and industry.This award is about the development of numerical simulations and models that predict the gravitational wave signals from black hole-neutron star and binary neutron star mergers, both in general relativity and alternative theories. As our gravitational wave detectors continue to improve, there is a need to improve our gravitational wave models that are used to compare against the observed data and to test general relativity in the strong field regime. This research addresses this pressing need by conducting novel numerical simulations of black hole-neutron star and binary neutron star mergers in general relativity as well as alternative theories like scalar-tensor gravity. This is followed by the construction of data-driven surrogate models that accurately reproduce the gravitational wave signal from the simulations. Such simulations and models are critical for reliably extracting the astrophysical source properties and testing general relativity using these observations.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.