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，并解决了NSF“宇宙之窗”大理念的优先领域。自2015年首次探测到两个黑洞合并产生的引力波以来，引力波天体物理学的新生领域正处于加速发展的轨道上，有数十个探测，包括黑洞，中子星星和混合中子星-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，并提供有关最强大的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潜在来源的仔细评估。该奖项侧重于由数据质量问题（称为故障）引起的系统不确定性。主要目标是对双星中黑洞的一些最难以捉摸的性质提供强有力的约束：它们的自旋和轨道的偏心率。该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伪影重叠，称为故障。过去的经验表明，第四次观测期间预计检测率的提高将导致更多此类重叠的情况，从而危及天体物理参数估计。现有的缓解技术的基础上建模和减去故障的结果在强大的推断黑洞的质量和自旋与轨道对齐。该奖项的目标是扩展故障缓解技术，以稳健地测量更微妙的物理效应，如轨道平面中的自旋（自旋进动）和轨道偏心率，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。该奖项处理偏心率和自旋旋进推理的数据质量问题存在沿着两个方面。第一个涉及到观察到的信号，该小组将使用传统的推理来研究在下一次观测运行及以后的合并主导信号中自旋进动和偏心率的现象学和可测量性。第二个转向检测器噪声，该小组将构建一种受天体物理学人口推断启发的新方法：他们使用检测器数据来推断各种毛刺家族的人口属性，然后通过使用毛刺人口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运行期间测量偏心率或自旋进动的可能性，这对数据质量问题是稳健的。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. 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.