通过融合传感器阵列抑制牛顿噪声
Silencing Newtonian noise using fusion sensor arrays
AI总结：
通过融合地震仪和DAS传感器阵列，有效抑制牛顿噪声，实现低成本高效率的引力波探测器噪声控制
摘要：
牛顿噪声（NN）来自地震密度波动，预计会限制第三代引力波探测器低频灵敏度，特别是爱因斯坦望远镜（ET）。当前NN抑制依赖于地震仪阵列和维纳滤波，而分布式声学传感（DAS）提供了一种互补的、低成本的获取密集应变测量的方法。我们研究了由位移测量地震仪和应变测量DAS型传感器组成的融合传感器阵列。我们扩展了维纳滤波形式化以适用于混合传感器类型，并引入了解析的S波应变相关系数。使用混合微分进化和协方差矩阵适应方案，我们验证了我们的方法与已建立的地震仪-only结果，并分析了优化融合阵列的几何形状、鲁棒性和性能。融合阵列增强了P/S波分离，并实现了与仅地震仪阵列相当甚至有时超过的NN消除水平，特别是在小传感器数量的情况下。当传感器被限制在ET基础设施内时，我们发现六台地震仪配合十四台应变计在ET臂内可以达到二十台地震仪在钻孔中的性能，残差在10%的水平，从而提供了一条成本效益高的ET级NN抑制途径。
英文摘要：
Newtonian noise (NN) from seismic density fluctuations is expected to limit the low-frequency sensitivity of third-generation gravitational-wave detectors, in particular the Einstein Telescope (ET). Current NN mitigation relies on seismometer arrays and Wiener filtering, while distributed acoustic sensing (DAS) offers a complementary, low-cost means of obtaining dense strain measurements. We investigate fusion sensor arrays composed of both displacement-measuring seismometers and strain-measuring DAS-type sensors. We extend the Wiener filter formalism to mixed sensor types and introduce analytic S-wave strain correlation coefficients. Using a hybrid differential evolution and covariance matrix adaptation scheme, we validate our approach against established seismometer-only results and analyze the geometry, robustness, and performance of optimized fusion arrays. Fusion arrays enhance P/S-wave disentanglement and achieve NN cancellation levels comparable to, and sometimes exceeding, those of seismometer-only arrays, particularly for small sensor numbers. When sensors are constrained to the ET infrastructure, we find that six seismometers complemented by fourteen strainmeters inside the ET arms can match the performance of twenty seismometers in boreholes, achieving a residual at the 10% level, and thereby offering a cost-efficient pathway toward ET-scale NN mitigation.
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