基于生物拓扑的量子计算算法优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Abstract: Quantum computing, a revolutionary paradigm in computation, holds immense potential across diverse fields, including drug discovery, materials science, and cryptography. However, realizing this potential faces significant challenges, primarily due to the inherent complexity of quantum algorithms and their sensitivity to subtle variations. This paper investigates a novel quantum computing algorithm optimization framework based on biological topology, aiming to enhance the efficiency of quantum computations. We introduce a framework leveraging the unique structural properties of biological networks to guide the optimization process, resulting in improved performance compared to traditional methods. The core mechanism centers around identifying and utilizing specific topological patterns within biological data to inform the design of quantum circuits. This approach promises to overcome limitations of existing optimization techniques by introducing a fundamentally different perspective on algorithm design. The study explores the potential of this approach through theoretical analysis and preliminary simulations, demonstrating its effectiveness in optimizing specific quantum circuit designs. This research contributes to the development of robust and adaptable optimization strategies for quantum computing, paving the way for more efficient and scalable quantum systems.

DOI: 10.5281/zenodo.22276561

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