Computational Analysis of Quantum Dot Cellular Automata: An Empirical Study on Error Mitigation Techniques

Abstract

Quantum Dot Cellular Automata (QDCA) has emerged as a promising paradigm in the field of computational systems, offering potential improvements in speed and miniaturization for future computing architectures. This study investigates the prevalent error states within QDCA during operation, focusing on the implementation of novel error mitigation techniques. Through a series of empirical experiments utilizing MATLAB R2023a and Python 3.9 with SciPy and NumPy libraries, we quantitatively measured the performance of various error correction algorithms. Our findings reveal a significant reduction in error rates by up to 35% when employing optimized error-correcting codes compared to traditional methods. We underscore the relevance of our results for future quantum computing systems, illustrating the empirical foundation for enhanced reliability in QDCA. This research contributes to the ongoing discourse on quantum computing reliability and presents critical insights for practitioners in computational science.