WoU-MMA: Expanding the Horizons of Gravitational Wave Searches and Parameter Estimation

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。在过去的五年里，LIGO-VIRGO合作已经从由黑洞和中子星组成的合并双星系统中检测到了几个引力波信号。这些观测已经对宇宙中恒星残骸的组装和演化产生了新的见解，目前这受到事件数量少的限制。在这种情况下，该奖项支持的研究将推动创新方法，以（a）了解和减轻限制搜索灵敏度的因素，（B）表征检测到的信号的属性。这种方法是对提高灵敏度的硬件改进的补充，通过帮助检测和表征最微弱和最遥远的信号，将有助于最大限度地提高LIGO-VIRGO观测的科学产量。由此产生的对源特性的快速和可靠的理解也将有助于更好地指导后续观测。该计划还将通过开发更广泛的专业知识来分析LIGO应变数据，发布更多衍生数据产品，吸引和参与当地本科生和高中生参与研究，以及组织更广泛领域的教学研讨会，促进NSF扩大引力波社区的长期愿景。研究计划有两个组成部分。第一个目的是表征和更好地减轻两个系统，已被证明会影响噪声背景，从而影响搜索的灵敏度：非常短的时间尺度毛刺在检测器中，这是已知的是非常本地化的参数空间，和温和的长期变化的噪声特性，这会影响恢复的事件的信噪比的精度。这些系统学以前已经确定，但与扩展的详细程度，将在这项研究中实现，它是可能的，以制定简单的措施，以遏制其影响，是现有方法的自然扩展（如信号质量否决权和重新加权信噪比）。第二个目标是改进现有的参数估计管道，以帮助快速和鲁棒地推断引力波源的内在和外在性质。该方法建立在利用信号的频率结构的现有代码（即，它们的相位随频率的平滑行为），以及来自搜索的关于如何将检测过程与局部仪器伪像隔离的见解，即，该奖项反映了NSF的法定使命，并被认为是值得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的支持。

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 the last five years, the LIGO-VIRGO collaboration has detected several gravitational wave signals from merging binary systems consisting of black holes and neutron stars. These observations are already yielding new insights into the assembly and evolution of stellar remnants in the Universe, which are currently limited by the low numbers of events. In this context, the award supports research that will push forward innovative methods to (a) understand and mitigate factors that limit the sensitivity of the searches, and (b) characterize the properties of the signals that are detected. This approach is complementary to hardware improvements that boost the sensitivity, and by helping to detect and characterize the faintest and most distant signals, will help maximize the scientific yield of the LIGO-VIRGO observations. The resultant rapid and robust understanding of the source properties will also help better guide subsequent observations. The program will also facilitate NSF’s long-term vision on expanding the gravitational wave community by developing broader expertise in analyzing the LIGO strain data, releasing more derived data products, engaging and involving local undergraduate and high school students in the research, and organizing a pedagogical workshop for the wider field. The research plan has two components. The first aim is to characterize and better mitigate two systematics that have been proven to affect the noise background, and consequently affect the sensitivity of searches: very short time-scale glitches in the detector, which are known to be extremely localized in parameter space, and moderate to longer-term variations in the noise characteristics, which affect the precision on the recovered signal-to-noise ratios of events. These systematics have been previously identified, but with the expanded level of detail that would be achieved in this research, it is possible to develop simple measures to curb their impact that are natural extensions of existing methods (such as signal-quality vetos and re-weighted signal-to-noise ratios). The second aim is to improve existing parameter estimation pipelines to help rapidly and robustly infer the intrinsic and extrinsic properties of gravitational wave sources. The methods build on existing codes that exploit the frequency structure of the signals (i.e., the smooth behavior of their phase with frequency), and insights from the searches on how to insulate the detection process from localized instrumental artifacts, i.e., glitches.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.