PMCHWT Solver Accelerated by Adaptive Cross Approximation for Efficient Computation of Scattering from Metal Nanoparticles
Abstract
:1. Introduction
2. Materials and Methods
2.1. Generic PMCHWT Formulation for a Metal Nanoparticle
2.2. Triangular–Triangular Cyclic Integral Method for Element Calculation of Impedance Matrix
2.3. The Octree Establishes Grouping
2.4. Overview of the Adaptive Cross Approximation (ACA) Algorithm
Algorithm 1. The detailed process of the ACA algorithm 
Initialization steps:

Next, the k th iteration:

2.5. ACA Algorithm Accelerates Filling Impedance Matrix
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Method  MoM  ACA 

HH polarization calculation time (s)  42.64  28.84 
VV polarization calculation time (s)  42.61  28.86 
Radius (nm)  68.25  456  

Method  MoM  ACA  MoM  ACA 
HH polarization calculation time (s)  41.30  27.90  45.22  30.37 
VV polarization calculation time (s)  41.19  27.47  44.61  30.57 
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Liu, Z.; Xi, L.; Bao, Y.; Cheng, Z. PMCHWT Solver Accelerated by Adaptive Cross Approximation for Efficient Computation of Scattering from Metal Nanoparticles. Micromachines 2022, 13, 1086. https://doi.org/10.3390/mi13071086
Liu Z, Xi L, Bao Y, Cheng Z. PMCHWT Solver Accelerated by Adaptive Cross Approximation for Efficient Computation of Scattering from Metal Nanoparticles. Micromachines. 2022; 13(7):1086. https://doi.org/10.3390/mi13071086
Chicago/Turabian StyleLiu, Zhiwei, Longfeng Xi, Yang Bao, and Ziyue Cheng. 2022. "PMCHWT Solver Accelerated by Adaptive Cross Approximation for Efficient Computation of Scattering from Metal Nanoparticles" Micromachines 13, no. 7: 1086. https://doi.org/10.3390/mi13071086