A Comparative Analysis of Quantum Entanglement in Hybrid Quantum-Classical Computing Architectures

Abstract

Recent advancements in quantum computing have highlighted the potential of hybrid quantum-classical architectures in solving complex computational problems. This study presents a comparative analysis of various approaches to harnessing quantum entanglement within these architectures. Utilizing both qualitative assessments and quantitative metrics, data was gathered from multiple sources, including simulations and real-world applications. Key findings reveal that while certain architectures yield higher entanglement rates, they often sacrifice coherence time. Our empirical methodology involved extensive simulations using Qiskit (version 0.24) and classical algorithms implemented in Python (version 3.9) to analyze entanglement fidelity and computational speed. The results indicate a significant trade-off between entanglement efficiency and operational stability, suggesting directions for future research in optimizing hybrid systems.