A computational inverse random source problem for elastic waves
By: Hao Gu , Tianjiao Wang , Xiang Xu and more
Potential Business Impact:
Find hidden earthquake causes from sound echoes.
This paper investigates the inverse random source problem for elastic waves in three dimensions, where the source is assumed to be driven by an additive white noise. A novel computational method is proposed for reconstructing the variance of the random source from the correlation boundary measurement of the wave field. Compared with existing multi-frequency iterative approaches, our method is non-iterative and requires data at only a single frequency. As a result, the computational cost is significantly reduced. Furthermore, rigorous error analysis is conducted for the proposed method, which gives a quantitative error estimate. Numerical examples are presented to demonstrate effectiveness of the proposed method. Moreover, this method can to be directly applied to stochastic Maxwell equations.
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