Integration of Quantum Computing and Classical Computing in Modern Systems

Abstract

The rapid development of computing technologies has highlighted the need for advanced computational paradigms capable of addressing complex and large-scale problems. Quantum computing has emerged as a promising technology with the potential to complement classical computing rather than completely replace it. This article aims to examine the integration of quantum computing and classical computing within modern computing systems. The research method employed is a literature review, analyzing scientific journals, reference books, and recent research publications related to hybrid quantum–classical computing architectures. The findings indicate that the integration of quantum and classical computing enables the development of hybrid systems that leverage the strengths of both paradigms, particularly in optimization, simulation, machine learning, and data processing applications. Classical computing remains essential for control, data preprocessing, and system orchestration, while quantum computing provides computational acceleration for specific tasks. However, challenges such as system interoperability, algorithm design, hardware limitations, and scalability persist. Therefore, effective integration strategies are crucial to maximize the benefits of quantum–classical hybrid systems in modern computing environments.