Design and Optimization of Optical NAND and NOR Gates Using Photonic Crystals and the ML-FOLD Algorithm - Alireza Mohammadi; Fariborz Parandin; Pouya Karami; Saeed Olyaee (Photonics)
The continuous demand for faster processing systems, driven by the rise of artificial intelligence, has exposed limitations in traditional transistor-based electronics, including quantum tunneling, heat dissipation, and switching delays due to challenges in further miniaturization. This study explores optical systems as a promising alternative, leveraging the speed of photons over electrons. Specifically, we design and simulate optical NAND and NOR logic gates using a two-dimensional photonic crystal structure with a square lattice. Symmetrical waveguides are used for the input paths to make the structure relatively more straightforward to fabricate. A key innovation is the ability to realize both gates within a single structure by adjusting the phases of the input sources. To optimize the phase parameters efficiently, we employ the ML-FOLD (Meta-Learning and Formula Optimization for Logic Design) optimization formula, which outperforms traditional methods and machine learning approaches in terms of computational efficiency and data requirements. Through finite-difference time-domain (FDTD) simulations, the proposed optical structure demonstrates successful implementation of NAND and NOR gate logic, achieving high contrast ratios of 4.2 dB and 4.8 dB, respectively. The results validate the effectiveness of the ML-FOLD method in identifying optimal configurations, offering a streamlined approach for the design of all-optical logic devices.