Performance analysis of the photonic crystal–based X-OR gate for the terahertz applications
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Rama Prabha Krishnamoorthy
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Robinson Savarimuthu
Abstract
A key component of high-speed switching networks is an optical logic gate. This study presents the design and analysis of an all-optical XOR gate based on a two-dimensional photonic crystal (2D PC) structure, aiming to enhance high-speed switching in optical networks. The XOR gate, with two input and one output waveguide, is constructed on a hexagonal lattice, optimized for operation at a wavelength of 1,550 nm. The design is evaluated using the Finite Difference Time Domain (FDTD) approach, which simulates the optical performance of the structure. Key performance metrics, including the bit rate, contrast ratio, and delay time, are computed, showing that the proposed logic gate achieves a high contrast ratio of 30.35 dB and a minimal delay time of 0.4 ps. The results confirm the potential of this all-optical XOR gate for integration into high-speed optical circuits, offering low power consumption and high efficiency. This work demonstrates the feasibility of utilizing photonic crystal structures for high-performance optical logic gates in future communication systems. The simplicity of fabrication in a two-dimensional photonic crystal (2D-PC)-based all-optical logic gate can often be attributed to its simple design.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors are responsible for the correctness of the statements provided in the manuscript. The following contributions have been made by the authors. RP calculated the structural parameters, such as radius of the rod, lattice constant, and refractive index, designed and simulated the proposed XOR gate. The electric field distribution, output response, bit rate, contrast ratio, response time are analyzed by RP. SR has given the idea, verified all the simulated results, and corrected the manuscript. Authors read and approved the final manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state that no conflicts of interest.
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Research funding: None declared.
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Data availability: The data that support the findings of this study are available from the authors, upon reasonable request.
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