Dynamic Analysis and Reservoir Computing Application of a Nonlinear Microring Resonator

Area of Science:

• Photonics and Optical Engineering
• Nonlinear Optics
• Computational Neuroscience

Background:

• Nonlinear microring resonators exhibit self-pulsing and memory effects crucial for neuromorphic computing.
• These resonators are utilized as nonlinear nodes in reservoir computing (RC) architectures.
• Previous methods for analyzing resonator dynamics and optimizing control parameters were computationally intensive.

Purpose of the Study:

• To develop a computationally efficient method for analyzing the dynamical behavior of nonlinear microring resonators.
• To identify optimal control parameters for efficient optical computation in RC systems.
• To predict the performance of microring resonators in RC applications without extensive simulations.

Main Methods:

• Governing differential equations for optical field, temperature, and free carrier concentration were analyzed.
• A linearization and stability analysis of the system was performed.
• An adiabatic approximation of the cavity field was used to calculate Jacobian eigenvalues.

Main Results:

• The linearization and stability analysis successfully identified regions in the control parameter space corresponding to different dynamical behaviors.
• Jacobian eigenvalues were calculated as reliable indicators of RC performance.
• The proposed method offers a significant reduction in computational cost compared to traditional simulations.

Conclusions:

• Linearization and stability analysis provide an efficient alternative to computationally intensive simulations for microring resonators.
• This approach enables faster identification of optimal operating regimes for neuromorphic applications.
• The findings facilitate the design and implementation of high-performance optical computing systems.