Gravitational-Wave Data Science with a LIGO at Caltech

该奖项支持引力波探测器调试和表征以及数据分析的研究，并解决了NSF“宇宙之窗”大构想的优先领域。引力波天文学已经进入了一个新的时代，当探测到的事件（到目前为止，来自紧凑的双星系统的合并：双黑洞和双中子星）将变得频繁。先进的LIGO探测器正在不断提高它们对gw的灵敏度；这将导致发现紧凑天体合并的空前速度，以及从其他天体物理来源发现许多gw的潜力。可能会发现全新种类的源。这些观测将促成天文学、宇宙学和基础物理学领域的大量研究和新的科学成果。对双黑洞合并的观测被用来理解恒星演化和双星的形成、演化和死亡。它们使广义相对论作为一种引力理论能够在强场、高度相对论性的环境中进行独特而有力的测试，在这种环境中产生了可探测的gw。对双中子星并合的观测使得对核状态方程的约束、对局部哈勃-勒梅特参数的独特测量、对伽马射线暴物理的研究以及对宇宙中重元素（包括金、铂和铀）起源的了解成为可能。所有这些研究都是通过极其灵敏的LIGO和Virgo探测器的建造和运行而实现的。加州理工学院的研究小组与LIGO实验室和LIGO科学合作组织（LSC）合作，不断提高探测器的灵敏度，精确校准应变数据，描述探测器的行为以评估和提高数据质量，并向公众发布数据。这些研究还主要依赖于利用高度优化的搜索管道，在嘈杂的数据中识别来自天体物理源的弱GW信号的能力。我们还使用分析LIGO数据所需的科学计算作为工具，吸引当地高中三年级和四年级学生学习引力波物理和天文学，通过实践GW数据科学项目引入编程并更广泛地应用科学方法。我们的工作是在LIGO O3和O4观测运行期间发现和分析LIGO、Virgo和KAGRA探测器的引力波信号。建议的工作重点是：(a)使用LSC的“旗舰”搜索管道PyCBC和gstlal，从LIGO， Virgo和KAGRA的数据中识别紧凑双星合并的GW信号；(b)使用隐马尔可夫模型Viterbi算法搜索来自紧密双星合并的长持续爆发GWs，来自银河系中新形成的快速旋转中子星的连续GWs (CGWs)，以及其他产生中心频率可能徘徊的窄带信号的源；(c)验证这些管道发现的候选事件（包括CGW候选事件），特别注意数据质量、校准和搜索管道细节。我们将以现有的专业知识和经验为基础，通过自动化日常任务，将其扩展到频繁检测的时代。我们将利用我们在低延迟数据处理，应变校准，探测器表征和数据质量评估以及搜索管道方面的专业知识。这些努力的结果将使我们能够自信地探测到频繁发生的GW事件，并使所获得的信息及时地提供给LSC、天文学界和公众，以便这些团体能够充分利用这些信息来推进引力波天文学。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 gravitational wave detector commissioning and characterization, as well as data analysis and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. Gravitational-wave (GW) astronomy has entered a new era, when detected events (so far, from the merger of compact binary systems: binary black holes and binary neutron stars) will become frequent. The Advanced LIGO detectors are continuously improving their sensitivity to GWs; this will result in unprecedented rates of discoveries of compact object mergers, and the potential for many discoveries of GWs from other astrophysical sources. Whole new classes of sources may be discovered. These observations will enable a wealth of studies and new scientific results in astronomy, cosmology, and fundamental physics. Observations of binary black hole mergers are used to understand stellar evolution and the formation, evolution and death of binaries. They enable uniquely powerful tests of general relativity as a theory of gravity in the strong-field, highly-relativistic regime where detectable GWs are produced. Observations of binary neutron star mergers enable constraints on the nuclear equation of state, unique measurements of the local Hubble-Lemaitre parameter, studies of gamma-ray burst physics, and insights into the origins of the heavy elements in the universe (including gold, platinum and uranium). All of these studies are made possible through the construction and operation of the incredibly sensitive LIGO and Virgo detectors. The Caltech group, working with the LIGO Laboratory and LIGO Scientific Collaboration (LSC), continuously improves the detectors' sensitivity, precisely calibrates the strain data, characterizes detector behavior to evaluate and improve data quality, and releases the data to the public. These studies also depend crucially on the ability to identify weak GW signals from astrophysical sources in the noisy data, using highly optimized search pipelines. We also use the scientific computing required to analyze LIGO data as a tool to engage high school juniors and seniors in the local area in gravitational-wave physics and astronomy, introducing programming and more broadly applying the scientific method through hands-on GW data science projects.Our work is devoted to discovering and analyzing gravitational-wave (GW) signals in the LIGO, Virgo and KAGRA detectors during LIGO's observing runs O3 and O4. The proposed work focuses on: (a) Identifying GW signals from compact binary mergers in data from LIGO, Virgo, and KAGRA, using both of the LSC ``flagship'' search pipelines, PyCBC and gstlal; (b) using the Hidden Markov Model Viterbi algorithm to search for long-duration burst GWs from compact binary mergers, continuous GWs (CGWs) from newly-formed, rapidly spinning neutron stars in our galaxy, and other sources that produce narrow-band signals with potentially wandering central frequency; and (c) validation of candidate events (including CGW candidates) found by these pipelines, with special attention to data quality, calibration, and search pipeline specifics. We will build on our existing expertise and experience in all of these efforts, and extend them to the era of frequent detections by automating routine tasks. We will exploit our expertise in low-latency data handling, strain calibration, detector characterization and data quality evaluation, and search pipelines. The results of these efforts will make it possible to make confident detections of GW events as they become frequent, and make the information obtained available to the LSC, to the astronomical community, and to the public, promptly, so that they can be fully exploited by those communities to advance gravitational-wave astronomy.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.