A butterfly-accelerated volume integral equation solver for broad permittivity and large-scale electromagnetic analysis
| Autor: | Yang Liu, Sadeed B Sayed, Abdulkadir Yucel, Luis Gomez |
|---|---|
| Přispěvatelé: | School of Electrical and Electronic Engineering |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
volume integral equation Communications Technologies Numerical Analysis (math.NA) fast solver Computer Science::Numerical Analysis Article Computational Engineering Finance and Science (cs.CE) preconditioners Direct Solver Butterfly Algorithm FOS: Mathematics Electrical and electronic engineering [Engineering] Mathematics - Numerical Analysis Electrical and Electronic Engineering Networking & Telecommunications Computer Science - Computational Engineering Finance and Science |
| Zdroj: | IEEE Trans Antennas Propag IEEE transactions on antennas and propagation, vol 70, iss 5 |
| Popis: | A butterfly-accelerated volume integral equation (VIE) solver is proposed for fast and accurate electromagnetic (EM) analysis of scattering from heterogeneous objects. The proposed solver leverages the hierarchical off-diagonal butterfly (HOD-BF) scheme to construct the system matrix and obtain its approximate inverse, used as a preconditioner. Complexity analysis and numerical experiments validate the $O(N\log^2N)$ construction cost of the HOD-BF-compressed system matrix and $O(N^{1.5}\log N)$ inversion cost for the preconditioner, where $N$ is the number of unknowns in the high-frequency EM scattering problem. For many practical scenarios, the proposed VIE solver requires less memory and computational time to construct the system matrix and obtain its approximate inverse compared to a $\mathcal{H}$ matrix-accelerated VIE solver. The accuracy and efficiency of the proposed solver have been demonstrated via its application to the EM analysis of large-scale canonical and real-world structures comprising of broad permittivity values and involving millions of unknowns. Nanyang Technological University This work was supported in part by Nanyang Technological University under a Startup Grant and in part by the National Institute of Mental Health of the National Institutes of Health under Award R00MH120046. The work of Yang Liu was supported in part by the U.S. Department of Energy, in part by the Office of Science, in part by the Office of Advanced Scientific Computing Research, and in part by the Scientific Discovery through Advanced Computing (SciDAC) Program through the FASTMath Institute at Lawrence Berkeley National Laboratory under Contract DE-AC02-05CH11231. |
| Databáze: | OpenAIRE |
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