Deep Underground Gravity Lab

该合同将支持南达科他州Homestake矿井地下地震仪阵列的运行。该阵列目前包括八个地震台站，探测矿井的可用深度和巨大的水平范围，每个台站都有一个高灵敏度宽带地震仪。该奖项将支持一名研究生，该研究生将在PI和合作者的监督下，对阵列进行必要的升级和维护，并确保阵列在两年的项目期间获得数据。该学生还将进行几个数据分析项目，包括地下地震噪声的初步研究，局部地震活动性的研究，以及地表对地震场内容和传播的影响。该阵列提供的独特数据将揭示地下地震运动的重要特征，如振幅、模态内容和岩石非均匀性的影响。对地下地震运动的充分了解对于物理中运动敏感实验的发展至关重要，例如引力波探测器或爱因斯坦广义相对论基础等效原理的测试。由于地球物理学和地震学团体对这些数据非常感兴趣，这些数据将通过“地震学联合研究机构”（IRIS）计划提供给这些团体。这些数据也将通过“理解宇宙的相互作用”（I2U2）计划提供给双子城地区的高中生，让他们接触到真实的数据，包括所有的细微之处和不完美之处，以及用于解决当今一些最复杂科学问题的大型计算资源。

This award will support operation of an underground seismometer array in the Homestake mine in South Dakota. The array currently includes eight seismic stations, probing the available depth and vast horizontal extent of the mine, each operating one high-sensitivity broadband seismometer. The award will support a graduate student who will, with supervision by the PI and collaborators, perform the necessary upgrades and maintenance of the array, as well as ensure acquisition of data by the array over the two-year project period. The student will also conduct several data analysis projects, including first studies of the underground seismic noise, studies of the local seismicity, and effects of the surface on the seismic field content and propagation.The unique data provided by this array will reveal important characteristics of the seismic motion underground such as its amplitude, modal content, and effects of rock non-uniformity. Good understanding of underground seismic motion will be crucial for the development of motion-sensitive experiments in physics, such as gravitational wave detectors or tests of the equivalence principle that underlies Einstein's theory of general relativity. Due to a very strong interest in this data among the geophysics and seismology communities, the data will be made available to these communities via the "Incorporated Research Institutions for Seismology" (IRIS) program. The data will also be made available to high-school students in the Twin Cities area through the "Interactions In Understanding the Universe" (I2U2) program, exposing them to the real data with all its subtleties and imperfections, and to the large computing resources that are used to solve some of the most complicated scientific problems today.