Paving the Way for the First Direct Gravitational-Wave Discovery through Improved Noise Budgeting and Detector Characterization

爱因斯坦发现的广义相对论告诉我们，我们日常所熟悉的引力其实是某种更奇怪的东西的表现：物质对时空几何形状的弯曲。该理论的关键预测包括宇宙膨胀和黑洞的存在，其中包括引力波（GW）的存在：在大质量的快速运动引起的时空几何中以光速运动的涟漪。虽然引力波对致密双星系统的间接影响已经得到了很好的验证，但直接探测地球上的引力波仍然是一个突出的挑战。实现这种能力的科学回报将是巨大的——从探测爆炸恒星的极端动力学到收集关于宇宙大爆炸时刻的状态的信息。这扇探索宇宙的新窗口耗费了数十年的实验和技术发展，突破了物理科学不同领域的界限。2015年将标志着引力波物理学备受期待的分水岭时刻：两个先进的激光干涉引力波天文台（aLIGO）探测器将开始它们的初始数据采集运行，随后是欧洲先进的处女座引力波天文台的调试。回路微调检测器的灵敏度将会加大成为十倍比第一代的探测器,开放的空间体积观察GW来源将比以前大1000倍。该奖项支持有助于aLIGO在未来几年实现设计灵敏度的研究，有助于对探测器的噪声源和特性进行更完整的描述。这将最终导致向公众发布具有可靠数据质量标志的GW数据。支持授权社区科学发现是这个项目的主要目标。此外，研究人员将继续与华盛顿州立大学普尔曼分校和三城分校的教师合作，通过讲座和实验练习向本科生讲授华盛顿大学的科学知识。后一个校区迎合了很大比例的西班牙裔和美洲原住民人口，这两个群体都是代表性不足的，并提供了一个罕见的环境，将大学教育与附近实验室进行的引力前沿研究结合起来。我们说话的时候，aLIGO探测器正在投入使用。这些宽带探测器还将探测来自多个来源的GW，如双黑洞，旋转非轴对称中子星，核心坍缩超新星，以及天体物理或宇宙学起源的随机GW背景。他们将通过解决其干涉测量测试质量光学的4公里距离的变化来实现这一目标，质量光学是一个原子大小的十亿分之一。威诺娜州立大学团队将整合多个新的传感器,安装在回路微调到模型的干涉噪声预算和工作在减少任何其预测和观察到的噪声地板之间的差距。

The General Theory of Relativity discovered by Einstein tells us that the familiar, everyday force of gravity is a manifestation of something much stranger: the bending of the geometry of space-time by matter. Among the key predictions of the theory, which includes the expanding Universe and the existence of black holes, is the existence of gravitational waves (GW): ripples moving at the speed of light in the geometry of space-time caused by the fast motion of large masses. Although well tested in terms of their indirect effects on binary systems of compact stars, the direct detection of gravitational waves incident on Earth poses an outstanding challenge. The scientific rewards from achieving this ability would be enormous - ranging from probing the extreme dynamics of exploding stars to gleaning information about the state of the Universe almost at the moment of the Big Bang itself. The effort to enable this new window on the universe has occupied several decades of experimental and technological developments that have pushed the boundaries across diverse fields in the physical sciences. The year 2015 will mark a highly-anticipated watershed moment for gravitational-wave physics: The two advanced Laser Interferomenter Gravitational Wave Observatory (aLIGO) detectors will start their initial data taking runs, followed by the commissioning of the advanced Virgo gravitational wave observatory in Europe. The sensitivity of the aLIGO detector will be ramped up to become about ten times better than that of the first-generation detectors, opening up a spatial volume for observing GW sources that will be 1000 times larger than before. This award supports research that helps aLIGO to achieve design sensitivity in the coming years by contributing to a more complete accounting of sources of noise and characterization of the detectors. This will eventually lead to the publishing of GW data to the public with robust data quality flags. Supporting scientific discoveries by empowering the community at large is a primary goal of this project. Additionally, the researchers will continue to engage the faculty of the WSU campuses in Pullman and Tri-Cities to teach undergraduate students about GW science both through lectures and lab exercises. The latter campus caters to a large percentage of Hispanic and Native-American populations, both of which are under-represented, and offers a rare setting for integrating university education with cutting-edge research in gravitation being carried out at a nearby lab.The aLIGO detectors are being commissioned as we speak. These broadband detectors will also target the detection of GWs from multiple sources, such as binary black holes, spinning non-axisymmetric neutron stars, core collapse supernovae, and stochastic GW background of astrophysical or cosmological origins. They will accomplish this by resolving changes in the 4-km separations of its interferometric test mass optics that are a billionth the size of an atom. The WSU team will integrate the multiple new sensors that have been installed in aLIGO into the model of the interferometer noise budget and work on reducing any gap between its prediction and the observed noise floor.