Strategies for global optimization in photonics design.

Area of Science:

• Photonics and Optical Engineering
• Computational Electromagnetics
• Materials Science

Background:

• Global optimization of photonic components often involves vast design spaces, leading to computationally intensive simulations.
• Efficient assessment of component designs and effective strategies for managing design space size are crucial for practical applications.

Purpose of the Study:

• To develop and evaluate a fast simulation method and matrix solver for photonic component design.
• To investigate strategies for controlling design space size in global optimization without compromising convergence.
• To analyze the impact of simulation approximations on optimization accuracy and runtime.

Main Methods:

• Analytical simulation based on Mie scattering.
• Fast matrix solver utilizing the fast multipole method.
• Integration with genetic algorithms (GAs) for global optimization.
• Examination of optimization strategies for waveguide bends (60° and 90°).

Main Results:

• A combined Mie scattering and fast multipole method significantly accelerates design assessment.
• Strategies for design space control were analyzed for their effectiveness in GA convergence.
• The trade-offs between simulation accuracy, runtime, and GA performance were quantified.
• Optimized photonic microstructures for waveguide bends were identified.

Conclusions:

• The proposed simulation and optimization framework enables efficient global optimization of photonic components.
• Controlling design space size is a viable strategy to reduce computational cost while maintaining optimization performance.
• The study provides practical insights and optimized designs for photonic waveguide bends.