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Determination of the Excitation and Coupling Rates Between Light Emitters and Surface Plasmon Polaritons

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Published on: July 21, 2018

Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

Yu Zhang, Osman S Ahmed, Mohamed H Bakr

|July 1, 2014

Summary

This summary is machine-generated.

We developed a new adjoint variable method to efficiently estimate how changes in nanoplasmonic device parameters affect performance. This method requires only one extra simulation, significantly reducing computational cost for sensitivity analysis.

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Area of Science:

Nanophotonics and Plasmonics
Computational Electromagnetics
Device Physics

Background:

Nanoplasmonic devices offer unique light-matter interactions.
Accurate sensitivity analysis is crucial for device optimization.
Current methods, like finite-difference time-domain (FDTD), can be computationally intensive.

Purpose of the Study:

To introduce an efficient adjoint variable method for sensitivity analysis in nanoplasmonics.
To reduce the computational cost associated with parameter sensitivity estimation.
To provide a versatile tool for optimizing nanoplasmonic device designs.

Main Methods:

Formulation of an adjoint variable method based on electric field components near discontinuities.
Computation of adjoint sensitivities using a single additional finite-difference time-domain (FDTD) simulation.
Application to an add-drop coupler with a square ring resonator.

Main Results:

The adjoint method accurately estimates sensitivities of arbitrary responses.
The number of parameters does not increase the number of required simulations.
Adjoint sensitivities for scattering parameters were computed and compared favorably to central finite difference results.

Conclusions:

The proposed adjoint variable method offers a computationally efficient alternative for nanoplasmonic device sensitivity analysis.
This approach facilitates faster optimization and design exploration of complex plasmonic structures.
The method's efficiency makes it suitable for high-throughput design and analysis workflows.