Leveraging continuous material averaging for inverse electromagnetic design

Area of Science:

• Electromagnetics
• Nanophotonics
• Computational Physics

Background:

• Inverse design optimizes device shape/topology for performance.
• Gradient computation is crucial but challenging for complex designs.
• Existing methods in nanophotonics face accuracy or design constraints.

Purpose of the Study:

• Introduce a novel strategy for efficient gradient computation in inverse electromagnetic design.
• Overcome limitations of previous shape and topology optimization approaches.
• Demonstrate the method's effectiveness in nanophotonic device design.

Main Methods:

• Developed a new strategy based on smoothing abrupt material interfaces.
• Enabled accurate gradient computation irrespective of simulation resolution.
• Applied the method to optimize a non-adiabatic waveguide taper.

Main Results:

• Achieved high accuracy in gradient computation.
• Optimized a waveguide taper, yielding a non-intuitive design.
• Demonstrated a very low insertion loss of 0.041 dB at 1550 nm.

Conclusions:

• The smoothing strategy offers an efficient and accurate approach for inverse electromagnetic design.
• This method overcomes key challenges in nanophotonic device optimization.
• The optimized waveguide taper showcases the practical benefits of the new technique.