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We present rigorous solutions of electromagnetics problems involving 3-D dielectric photonic crystals (PhCs). Problems are formulated with recently developed surface integral equations and solved iteratively using the multilevel fast multipole algorithm (MLFMA). For efficient solutions, iterations are accelerated via robust Schur-complement preconditioners. We show that complicated PhC structures...
In this paper, we consider solutions of a real-life dielectric problem using CTF and JMCFIE formulations. We offer two novel preconditioners, namely ASP and ISP, to overcome the convergence problem. The matrix equation obtained from JMCFIE benefits more from preconditioning and it is solved faster than the one obtained from CTF. However, a comparison of the near-zone fields shows that solutions obtained...
We propose direct and iterative versions of approximate Schur preconditioners to increase robustness and efficiency of iterative solutions of dielectric problems formulated with surface integral equations. The performance of these preconditioners depends on the availability of fast and approximate solutions to reduced matrix systems. We show that sparse-approximate-inverse techniques provide a suitable...
We consider fast and accurate solutions of electromagnetics problems involving three-dimensional photonic crystals (PhCs). Problems are formulated with the combined tangential formulation (CTF) and the electric and magnetic current combined-field integral equation (JMCFIE) discretized with the Rao-Wilton-Glisson functions. Matrix equations are solved iteratively by the multilevel fast multipole algorithm...
The author consider effective preconditioning of recently proposed two integral-equation formulations for dielectrics; the combined tangential formulation (CTF) and the electric and magnetic current combined-field integral equation (JMCFIE). These two formulations are of utmost interest since CTF yields more accurate results and JMCFIE yields better-conditioned systems than other formulations.
In this paper, we consider efficient parallelization of the sparse approximate inverse (SAI) preconditioner in the context of the multilevel fast multipole algorithm (MLFMA). Then, we report the use of SAI in the solution of very large EFIE problems. The SAI preconditioner is important not only because it is a robust preconditioner that renders many difficult and large problems solvable, but also...
When the target problem is small in terms of the wavelength, simple preconditioners, such as BDP, may sufficiently accelerate the convergence. On the other hand, for large-scale problems, the matrix equations become much more difficult to solve, and therefore, the importance of preconditioning become more evident for both formulations. In this paper, we demonstrate the use of novel, strong, and efficient...
We propose novel parallel preconditioning schemes for the iterative solution of integral equation methods. In particular, we try to improve convergence rate of the ill-conditioned linear systems formulated by the electric-field integral equation, which is the only integral-equation formulation for targets having open surfaces. For moderate-size problems, iterative solution of the near-field system...
We report the solution of the largest integral- equation problems in computational electromagnetics. We consider matrix equations obtained from the discretization of the integral-equation formulations that are solved iteratively by employing parallel multilevel fast multipole algorithm (MLFMA). With the efficient parallelization of MLFMA, scattering and radiation problems with millions of unknowns...
We report the solution of extremely large integral-equation problems involving electromagnetic scattering from conducting bodies. By orchestrating diverse activities, such as the multilevel fast multipole algorithm, iterative methods, preconditioning techniques, and parallelization, we are able to solve scattering problems that are discretized with tens of millions of unknowns. Specifically, we report...
For efficient solutions of integral-equation methods via the multilevel fast multipole algorithm (MLFMA), effective preconditioners are required. In this paper we review appropriate preconditioners that have been used for sparse systems and developed specially in the context if MLFMA. First we review the ILU-type preconditioners that are suitable for sequential implementations. We can make these preconditioners...
In this work, we propose a preconditioner that approximates the dense system operator. For this purpose, we develop an approximate multilevel fast multipole algorithm (AMLFMA), which performs a much faster matrix-vector multiplication with some relative error compared to the original MLFMA. We use AMLFMA to solve a closely related system, which makes up the preconditioner. Then, this solution is embedded...
We propose an effective preconditioning scheme for the iterative solution of the systems formulated by the electric- field integral equation (EFIE). EFIE is notorious for producing difficult-to-solve systems. Especially, if the target is complex and the utilized frequency is high, it becomes a challenge to solve these dense systems with even robust solvers such as full GMRES. For this purpose, we...
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