An efficient hybrid MLFMA-FFT solver for the volume integral equation in case of sparse 3D inhomogeneous dielectric scatterers

  • Authors:
  • J. De Zaeytijd;I. Bogaert;A. Franchois

  • Affiliations:
  • Department of Information Technology (INTEC), Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Gent, Belgium;Department of Information Technology (INTEC), Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Gent, Belgium;Department of Information Technology (INTEC), Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Gent, Belgium

  • Venue:
  • Journal of Computational Physics
  • Year:
  • 2008

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Abstract

Electromagnetic scattering problems involving inhomogeneous objects can be numerically solved by applying a Method of Moments discretization to the volume integral equation. For electrically large problems, the iterative solution of the resulting linear system is expensive, both computationally and in memory use. In this paper, a hybrid MLFMA-FFT method is presented, which combines the fast Fourier transform (FFT) method and the High Frequency Multilevel Fast Multipole Algorithm (MLFMA) in order to reduce the cost of the matrix-vector multiplications needed in the iterative solver. The method represents the scatterers within a set of possibly disjoint identical cubic subdomains, which are meshed using a uniform cubic grid. This specific mesh allows for the application of FFTs to calculate the near interactions in the MLFMA and reduces the memory cost considerably, since the aggregation and disaggregation matrices of the MLFMA can be reused. Additional improvements to the general MLFMA framework, such as an extention of the FFT interpolation scheme of Sarvas et al. from the scalar to the vectorial case in combination with a more economical representation of the radiation patterns on the lowest level in vector spherical harmonics, are proposed and the choice of the subdomain size is discussed. The hybrid method performs better in terms of speed and memory use on large sparse configurations than both the FFT method and the HF MLFMA separately and it has lower memory requirements on general large problems. This is illustrated on a number of representative numerical test cases.