Enhancing the Discovery Potential of Merging Black Holes with Robust Extraction of Spin-Precession and Eccentricity

该奖项支持相对论和相对论天体物理学的研究，它解决了NSF“宇宙之窗”大构想的优先领域。自2015年首次探测到两个黑洞合并产生的引力波以来，新生的引力波天体物理学领域正处于加速发展的轨道上，其中包括黑洞、中子星和混合中子星-黑洞双星。这一惊人的进展是由LIGO/Virgo探测器灵敏度的提高和分析技术的进步推动的。第四次观测活动将使探测数量增加四倍以上，并提供有关最强大天文事件的丰富信息。这些丰富的信息将回答有关黑洞的关键问题，但也带来了新的挑战：这种精确的测量必须伴随着对系统误差的潜在来源的仔细评估。该奖项侧重于由数据质量问题引起的系统不确定性，即所谓的小故障。主要目标是为双星黑洞的一些最难以捉摸的特性提供强有力的约束：它们的自旋和轨道的偏心率。这个项目的重点是来自黑洞和中子星的引力波信号，这些信号与探测器中的仪器工件重叠，被称为故障。过去的经验表明，在第四次观测期间预期的探测率的增加将导致更多的这种重叠的情况，从而危及天体物理参数的估计。现有的基于建模和减除故障的缓解技术可以可靠地推断出黑洞质量和与轨道对齐的自旋。该奖项的目标是扩展故障缓解技术，以可靠地测量更细微的物理效应，如轨道平面上的自旋（自旋进动）和轨道偏心，这些效应可以提供有关致密双星天体物理形成环境的宝贵信息。该奖项在两个方面解决了数据质量问题中存在的偏心和自旋进动推断。第一个与观测到的信号有关，在接下来的观测中，该小组将使用传统的推理来研究自旋进动和离心率的现象学和可测量性，这些信号来自合并主导的信号。第二个转向探测器噪声，该小组将构建一种受天体物理种群推断启发的新方法：他们使用探测器数据来推断各种故障族的种群属性，然后通过使用故障种群分布作为先验来获得边缘化数据质量问题的源推断。这项工作增加了在第四次观测期间测量偏心或自旋进动的可能性，这对数据质量问题是可靠的。该奖项反映了美国国家科学基金会的法定使命，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. Since the first detection of gravitational waves from the coalescence of two black holes in 2015, the nascent field of gravitational wave astrophysics is on an accelerating trajectory with dozens more detections, including black hole, neutron star, and mixed neutron star-black hole binaries. This spectacular progress is driven by the improving sensitivity of the LIGO/Virgo detectors and advances in analysis techniques. The fourth observing campaign will more than quadruple the number of detections and offer a wealth of information about the most powerful astronomical events. This wealth of information will answer key questions about black holes, but also bring new challenges: such precise measurements must be accompanied by a careful assessment of potential sources of systematic errors. This award focuses on systematic uncertainties originating by issues with the quality of data, known as glitches. The main goal is to provide robust constraints on some of the most elusive properties of black holes in binaries: their spins and the eccentricity of their orbit.This project focuses on gravitational wave signal from black holes and neutron stars that overlap with instrumental artifacts in the detectors, known as glitches. Past experience indicates that the increased rate of detection expected during the fourth observing run will result in more instances of such overlaps that jeopardize astrophysical parameter estimation. Existing mitigation techniques based on modeling and subtracting the glitch result in robust inference of black hole masses and spins aligned with the orbit. The goal in this award is to extend glitch-mitigation techniques to robustly measure more subtle physical effects such as spins in the orbital plane (spin-precession) and orbital eccentricity, effects that can provide invaluable information about the astrophysical formation environment of compact binaries. This award tackles eccentricity and spin-precession inference in the presence of data quality issues along two fronts. The first relates to the observed signals where the group will use traditional inference to study the phenomenology and measurability of spin-precession and eccentricity from merger-dominated signals in the next observing run and beyond. The second turns to the detector noise where the group will construct a novel approach that is inspired by astrophysical population inference: they use detector data to infer the population properties of various glitch families and then obtain source inference that marginalizes over data quality issues by using the glitch population distributions as priors. This work increases the likelihood of a measurement of eccentricity or spin-precession during the fourth observing run that is robust against data quality issues.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.