PMCHWT Solver Accelerated by Adaptive Cross Approximation for Efficient Computation of Scattering from Metal...

Area of Science:

• Computational electromagnetics
• Nanophotonics
• Numerical methods

Background:

• Calculating light scattering from metal nanoparticles is crucial for nanophotonics applications.
• Traditional methods like the Method of Moments (MoM) can be computationally intensive.

Purpose of the Study:

• To develop an accelerated algorithm for efficient light scattering calculations of single metal nanoparticles.
• To reduce the computational time and memory requirements of existing MoM approaches.

Main Methods:

• The Poggio-Miller-Chang-Harrington-Wu-Tsai (PMCHWT) integral equations were transformed into linear algebraic equations using the Method of Moments (MoM).
• The Rao-Wilton-Glisson (RWG) basis functions were employed for the near-field MoM impedance matrix elements.
• The Adaptive Cross Approximation (ACA) algorithm, utilizing an octree data structure, was applied to compress the far-field MoM impedance matrix, exploiting its low-rank property.

Main Results:

• The proposed algorithm significantly reduces impedance matrix filling time compared to traditional MoM.
• The ACA compression leads to a substantial decrease in solution time and memory usage.
• Numerical results confirm the accuracy and efficiency of the accelerated method for scattering field computation.

Conclusions:

• The ACA-accelerated MoM provides an accurate and efficient solution for light scattering from metal nanoparticles.
• This approach offers a significant improvement over traditional MoM, enabling faster computations.
• The method is well-suited for analyzing scattering phenomena in nanophotonic systems.