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The application of the generalized product-type method based on Bi-CG to accelerate the sparse-matrix/canonical grid method

机译:基于Bi-CG的广义乘积型方法在加速稀疏矩阵/规范网格方法中的应用

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When the sparse-matrix/canonical grid (SMCG) method is applied to analyse scattering of randomly positioned dielectric spheroids, the impedance matrix is decomposed into a strong interaction matrix and a weak interaction matrix. The strong interaction portion of the matrix-vector multiplication is computed directly as the moment method (MOM). The far-interaction portion of matrix-vector multiplication is computed indirectly using fast Fourier transforms by a Taylor series expansion of impedance matrix elements about the canonical grid point. However, the condition number of the impedance matrix obtained from the SMCG method becomes large compared to the one from MOM. As a result, the conjugate gradient (CG) method converges slowly. To attack such a trouble, the generalized product-type method based on Bi-CG (GPBi-CG) is used as an iterative solver in this paper. The numerical results show that the GPBi-CG method can achieve good convergence improvement compared to the other iterative methods.
机译:当使用稀疏矩阵/规范网格(SMCG)方法分析随机放置的介电球体的散射时,阻抗矩阵被分解为强相互作用矩阵和弱相互作用矩阵。矩阵矢量乘法的强相互作用部分直接作为矩量法(MOM)计算。矩阵矢量乘法的远交互作用部分是使用快速傅里叶变换通过阻抗矩阵元素围绕规范网格点的泰勒级数展开间接计算的。但是,与从MOM获得的阻抗矩阵的条件数相比,从SMCG获得的阻抗矩阵的条件数变大。结果,共轭梯度(CG)方法收敛缓慢。为了解决这种问题,本文将基于Bi-CG的广义乘积类型方法(GPBi-CG)用作迭代求解器。数值结果表明,与其他迭代方法相比,GPBi-CG方法具有较好的收敛性。

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