论文标题

反介质问题的自适应光谱分解

Adaptive spectral decompositions for inverse medium problems

论文作者

Baffet, Daniel H., Grote, Marcus J., Tang, Jet Hoe

论文摘要

逆介质问题涉及通过探索可能解决方案的受限搜索空间来重建可用观察结果的空间变化的未知介质。基于标准网格的表示非常笼统,但由于搜索空间的高维度,通常在计算上都太过于刺激了。自适应光谱(AS)分解是在明智的椭圆算子的特征函数的基础上扩展未知介质的,该椭圆算子依赖于培养基。在这里,AS分解与标准不推动的牛顿型方法相结合,用于解决由Helmholtz方程控制的时谐波散射问题。通过反复调整征函数基础及其维度,所得的自适应光谱反演(ASI)方法大大降低了非线性优化期间搜索空间的尺寸。对于一般的分段常数介质,证明了AS分解的严格估计值。数值结果说明了时间谐波逆散射问题的ASI方法的准确性和效率,包括来自地球物理的盐圆顶模型。

Inverse medium problems involve the reconstruction of a spatially varying unknown medium from available observations by exploring a restricted search space of possible solutions. Standard grid-based representations are very general but all too often computationally prohibitive due to the high dimension of the search space. Adaptive spectral (AS) decompositions instead expand the unknown medium in a basis of eigenfunctions of a judicious elliptic operator, which depends itself on the medium. Here the AS decomposition is combined with a standard inexact Newton-type method for the solution of time-harmonic scattering problems governed by the Helmholtz equation. By repeatedly adapting both the eigenfunction basis and its dimension, the resulting adaptive spectral inversion (ASI) method substantially reduces the dimension of the search space during the nonlinear optimization. Rigorous estimates of the AS decomposition are proved for a general piecewise constant medium. Numerical results illustrate the accuracy and efficiency of the ASI method for time-harmonic inverse scattering problems, including a salt dome model from geophysics.

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