Optical XOR logic gate design in two dimensional photonic crystal using ANN and PSO

Area of Science:

• Photonics
• Optical Computing
• Materials Science

Background:

• All-optical logic gates are crucial for high-speed optical computing.
• Photonic crystals (PCs) offer a promising platform for integrated optical devices.
• Optimization of PC-based devices is essential for practical applications.

Purpose of the Study:

• To design and optimize an all-optical XOR gate using two-dimensional photonic crystals.
• To leverage artificial neural networks (ANN) and particle swarm optimization (PSO) for performance enhancement.
• To demonstrate a viable strategy for complex optical computing systems.

Main Methods:

• Utilized the Finite-Difference Time-Domain (FDTD) method to generate a dataset of 555 samples.
• Employed an artificial neural network (ANN) to model the XOR gate's behavior.
• Applied particle swarm optimization (PSO) to optimize key design parameters like lattice constant and rod radius.

Main Results:

• Achieved an optimized all-optical XOR gate structure.
• Demonstrated output powers of 0 (0), 0.995 (1), 0.935 (1), and 0.015 (0) for logical states.
• Obtained a contrast ratio of 17.947 dB, indicating acceptable performance.

Conclusions:

• The ANN-PSO approach effectively optimizes photonic crystal designs for enhanced performance.
• The developed all-optical XOR gate shows potential for advanced optical computing and logic applications.
• This work presents a promising strategy for developing efficient and complex photonic computing systems.