Improving the Accuracy, Robustness, and Computational Efficiency of the Spinning, Precessing Effective-One-Body Numerical-Relativity (SEOBNRv3/SEOBNRv4P) Codes

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。为了检测和表征Advanced LIGO观测到的引力波信号，需要理论模型来预测信号作为源参数的函数的详细行为。这些模型必须提供爱因斯坦方程的精确解的精确近似，但也必须是快速和鲁棒的可计算的，以便它们可以用于预测数亿个参数位置的信号，以表征单个事件。为此，该项目将在准确和有效的波形模型方面创造新的最先进的技术，从而有助于确保未来的高级LIGO观测不受所使用的波形模型的限制。除了科学上的好处外，这项工作还将培训一名研究生掌握分析相对论和引力波数据分析的最佳做法，从而帮助培训下一代引力波天文学家。最后，这项建议将有助于促进在整个西弗吉尼亚州开展有影响力的教育和外联活动，具体做法是通过编制关于引力波天体物理学的新介绍，为现有的空间公共外联小组方案作出贡献。（SEOBNRv3，和目前正在开发的SEOBNRv4P）重力波形模型是仅有的两个模型之一（沿着IMRPhenomP）能够促进黑洞二元事件的完整参数估计（PE）。然而，尽管与数值相关性波形相比，它们具有很高的效率和可靠性，但原始的SEOBNR代码仍然太慢，无法直接用于基于标准马尔可夫链蒙特卡罗（MCMC）的PE。为了解决这个问题，PI的团队之前开发了SEOBNR近似的优化版本，这使得使用SEOBNRv3_opt可以更快地对候选事件执行PE。此外，SEOBNRv3_opt的开发揭示了潜在SEOBNRv3近似物中的偶然病理行为。虽然每10，000到100，000例中仅发生一次，但该频率仍然是PE的主要障碍，因为PE需要生成10^8个波形实现。因此，迫切需要开发比SEOBNRv3_opt显著更有效并且实质上更鲁棒的近似。该项目将创建一个新的国家的最先进的近似，这是更准确和更强大的比任何目前存在的。这将需要首先基于SEOBNRv3_opt创建一个新的近似，但用PI开发的后向单体（BOB）合并器振铃模型替换振铃附件，该模型在NR探测的整个参数空间范围内产生与NR结果一样准确的合并器振铃波形。由于BOB可以扩展到比光环更早的时间，它可以避免SEOBNRv3对光环精确位置的极端敏感性，从而大大提高了模型的鲁棒性。该奖项反映了NSF的法定使命，并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，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. In order to detect and characterize the gravitational-wave signals observed by Advanced LIGO, theoretical models that predict the detailed behavior of the signal as a function of the source parameters are required. These models must provide an accurate approximation to the exact solution of Einstein's equations, but must also be rapidly and robustly calculable, so that they can be used to predict the signal at hundreds of millions of parameter locations in order to characterize a single event. To that end, this project will create a new state-of-the-art in accurate and efficient waveform models, thus helping to ensure that future Advanced LIGO observations are not limited by the waveform models being used. In addition to the scientific benefits, this work will result in the training of a graduate student in the best practices of analytical relativity and gravitational-wave data analysis, thereby helping to train the next generation of gravitational-wave astronomers. Finally, this proposal will help facilitate impactful education and outreach throughout the state of West Virginia, by contributing to the existing Space Public Outreach Team (SPOT) program through the development of a new presentation on gravitational-wave astrophysics.The Precessing Spinning Effective-One-Body Numerical-Relativity (SEOBNRv3, and SEOBNRv4P currently under development) gravitational waveform model is one of only two models (along with IMRPhenomP) capable of facilitating complete parameter estimation (PE) of black-hole binary events. However, despite their great efficiency and reliability when compared to numerical relativity waveforms, the original SEOBNR codes were still far too slow to be directly useful for standard Markov-Chain Monte Carlo (MCMC)-based PE. To address this issue, the PI's team previously developed optimized versions of the SEOBNR approximants, which make it possible, using SEOBNRv3_opt, to perform PE on a candidate event at a much faster rate. In addition, the development of SEOBNRv3_opt uncovered occasional pathological behavior in the underlying SEOBNRv3 approximant. While only occurring in one out of every ~10,000 to 100,000 cases, this frequency nonetheless presents a major obstacle to PE, which requires the generation of 10^8 waveform realizations. Therefore, there is an urgent need to develop an approximant that is both significantly more efficient than SEOBNRv3_opt, and also substantially more robust. This project will create a new state-of-the-art approximant that is both more accurate and more robust than any currently in existence. This will require, first, the creation of a new approximant based on SEOBNRv3_opt, but replacing the ringdown attachment with the Backwards One-Body (BOB) merger-ringdown model developed by the PI, which produces merger-ringdown waveforms as accurate as NR results across the entire range of parameter space probed by NR. Because BOB can be extended to earlier times than the light ring, it can avoid the extreme sensitivity of SEOBNRv3 to the exact light ring location, thereby dramatically improving the robustness of the model.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.