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Design and Optimization of a Photonic Crystal-Based All-Optical XOR Gate Using Machine Learning

عنوان مقاله: Design and Optimization of a Photonic Crystal-Based All-Optical XOR Gate Using Machine Learning
شناسه ملی مقاله: JR_MJEE-18-1_001
منتشر شده در در سال 1403
مشخصات نویسندگان مقاله:

Fariborz Parandin - Department of Electrical Engineering, Islamic Azad University, Kermanshah Branch, Kermanshah, Iran
Alireza Mohamadi - Department of Computer Engineering, Islamic Azad University, Kermanshah Branch, Kermanshah, Iran

خلاصه مقاله:
In this article, a two-dimensional photonic crystal-based XOR gate is designed and simulated. For this purpose, an initial two-dimensional photonic crystal structure is chosen and waveguides are created for inputs and outputs. Then, defect rods are selected so that the obtained outputs are approximately consistent with the XOR gate truth table. After that, we will be looking for the best output so that the highest optical power is created for logic ۱ and the lowest power in the logical state of ۰. For this reason, the simulation is performed for four defect rods and the output is obtained for different the radius of the rods. Then, using the K-Nearest Neighbors algorithm, which is a machine learning algorithm, the best output for logic ۰ and also for logic ۱ is obtained. The results show that the designed logic gate has high output power in logic ۱ and very low power in the logic ۰ state.

کلمات کلیدی:
Optical XOR gate, photonic bandgap, Photonic Crystal, K-Nearest Neighbors

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1967087/