Gravitational-Wave Inference from Binary Compact Objects

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。引力波为天文学提供了新的工具。爱因斯坦在1916年首次预测，直到世纪高级LIGO的发展，它们的直接观测才成为可能。引力波使我们能够研究宇宙中一些最极端的系统，例如两个黑洞或中子星的合并，否则这些系统将对我们隐藏起来。在最初的两次观测中，高级LIGO探测器网络发现了10个双黑洞合并和一个双中子星星合并的引力波。在未来的运行中，检测速度将加快，每隔几天就会发现二进制文件。这些独特的观测将使我们能够回答天体物理学中长期存在的问题，例如：黑洞的质量是多少？黑洞和中子星的双星是如何形成的？大质量恒星是如何爆炸并留下黑洞或中子星星残骸的？黑洞的数量会随着宇宙的演化而变化吗？中子星星合并在锻造像金这样的重元素中扮演什么角色？要回答这些问题，需要可靠和有效的技术来分析迅速增长的引力波数据。该研究项目支持开发尖端统计技术，以提取引力波数据中编码的信息，并利用这些信息揭开黑洞和中子星星双星的核心奥秘。具体而言，有两个主要研究目标：（i）更有效地从引力波信号推断并合双星的物理参数（通过改进采样算法和自动化），（考虑到现实的、非平稳的和非高斯的噪声，并考虑到我们目前的引力波模型中缺失的物理现象，如偏心率）;（ii）使用参数和非参数模型，从探测的总体中进行总体推断，以重建合并二进制的分布（在质量，自旋和红移方面），并将结果与天体物理模型进行比较，以限制目前不确定的双星演化物理学（如共同包络效率和超新星踢）。开发的推理工具将公开提供，以使引力波天文学在频繁探测的时代迅速发展。此外，引力波天文学的最新成果和多信使天文学的兴奋，将通过一系列的外联活动，从天文馆活动到科普写作传达给不同的观众。该奖项反映了NSF的法定使命，并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. Gravitational waves offer a new tool for astronomy. First predicted by Einstein in 1916, their direct observation was only made possible a century later with the development of Advanced LIGO. Gravitational waves allow us to study some of the Universe's most extreme systems, such as the mergers of two black holes or neutron stars, which would otherwise remain hidden from us. In its first two observing runs, the Advanced LIGO detector network discovered gravitational waves from 10 binary black hole mergers and one binary neutron star merger. In future runs, the rate of detections will accelerate, with binaries being found every few days. These unique observations will enable us to answer long-standing questions in astrophysics like: What are masses of black holes? How are binaries of black holes and neutron stars made? How do massive stars explode and leave black hole or neutron star remains? Does the population of black holes change as the Universe evolves? What role do neutron star mergers play in forging heavy elements like gold? To answer these questions requires reliable and efficient techniques to analyse the rapidly growing collection of gravitational-wave data. The research supported by this grant supports the development of cutting edge statistical techniques to extract the information encoded in gravitational-wave data, and use this the unravel the central mysteries of black hole and neutron star binaries.Specifically, two main research objectives are targeted: (i) Inferring the physical parameters of merging binaries from gravitational-wave signals more efficiently (through improvements to sampling algorithms and through automation) and more accurately (accounting for realistic, non-stationary and non-Gaussian noise, and accounting for missing physics, such as eccentricity, in our current gravitational-wave models); (ii) Performing population inferences from the ensemble of the detections, using parametric and non-parametric models to reconstruct distributions of merging binaries (in terms of masses, spins and redshifts), and comparing results to astrophysical models to constrain the currently uncertain physics of binary evolution (such as common-envelope efficiency and supernova kicks). The inference tools developed will be made publicly available to enable the rapid advancement of gravitational-wave astronomy in the era of frequent detections. Furthermore, the latest results of gravitational-wave astronomy, and the excitement of multimessenger astronomy, will be communicated to diverse audiences through a range of outreach activities ranging from planetarium events to popular science writing.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.