Advancement in Quantum Computing: Bridging the Gap Between Theoretical Models and Practical Application
Keywords:
Quantum Computing, Theoretical Models, Practical Applications, Interdisciplinary Approaches, Quantum AlgorithmsAbstract
This paper provides a comprehensive examination of the progression and challenges in the field of quantum computing, with a specific focus on bridging the theoretical foundations with practical applications. Beginning with a historical perspective, it traces the evolution of quantum computing from its conceptual roots to its current advancements, highlighting key theoretical models such as Quantum Turing Machines, Quantum Circuits, and Quantum Annealing. The methodology involves a detailed analysis of recent breakthroughs in quantum computing, utilizing case studies in areas like quantum machine learning, biochemical system simulations, and optimization problems to demonstrate the practical implementation of theoretical models. The results underscore the significant strides made in applying quantum computing to real-world problems, despite the challenges of quantum decoherence, scalability, and integration with classical computing systems. The paper discusses interdisciplinary strategies, combining insights from computer science, physics, and engineering, as crucial for overcoming these hurdles. It emphasizes the importance of collaborative research, investment in quantum hardware, advancement of quantum software, and educational initiatives to cultivate expertise in this emerging field
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