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  4. Vol 10, Issue 1, 2025

Hybrid Quantum-Classical Computing for Physical Problems: Architectures, Algorithms, and Applications in the Networked Era

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DOI: 10.23977/jnca.2025.100109 | Downloads: 7 | Views: 249

Author(s)

Baixin Pan 1

Affiliation(s)

1 The University of Hong Kong, Hong Kong, China

Corresponding Author

Baixin Pan

ABSTRACT

This report provides a comprehensive analysis of hybrid quantum-classical computing's role in addressing complex physical problems. It delineates the foundational principles of both classical and quantum paradigms, explores advanced architectural models and integration strategies, and details the application of cutting-edge quantum algorithms—including Variational Quantum Eigensolver (VQE), Quantum Phase Estimation (QPE), and Quantum Approximate Optimization Algorithm (QAOA)—alongside classical numerical methods such as Finite Element Method (FEM) and Finite Difference Method (FDM). Through a review of real-world case studies in materials science, chemistry, fluid dynamics, and high-energy physics, the report illustrates the transformative potential of this synergistic approach. Furthermore, it critically examines the prevailing challenges, encompassing hardware limitations, quantum error correction, software-hardware co-design, scalability, and data handling complexities, while forecasting the convergence with exascale computing. The aim is to elucidate the current state and future trajectory of hybrid quantum-classical computing as a pivotal tool for scientific discovery and engineering innovation in the networked era.

KEYWORDS

Hybrid Quantum-Classical Computing, Physical Problems, Quantum Algorithms, High-Performance Computing, Quantum Error Correction, Computational Physics, Materials Science, Fluid Dynamics, High-Energy Physics, Optimization

CITE THIS PAPER

Baixin Pan, Hybrid Quantum-Classical Computing for Physical Problems: Architectures, Algorithms, and Applications in the Networked Era. Journal of Network Computing and Applications (2025) Vol. 10: 70-80. DOI: http://dx.doi.org/10.23977/jnca.2025.100109.

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