Self-Adaptive Quantum Topology Dynamic Optimization Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum topology, a novel framework for manipulating quantum states, offers unprecedented opportunities for algorithm design and optimization. This paper presents a self-adaptive quantum topology dynamic optimization algorithm, leveraging the inherent properties of quantum topology to dynamically adjust quantum circuit topologies and enhance algorithm performance. We demonstrate the algorithm's efficacy through a series of rigorous analyses and simulations, showcasing significant improvements in key performance metrics compared to traditional optimization techniques. The core mechanism centers around the continuous exploration and refinement of quantum topology through iterative adjustments, effectively circumventing the limitations of static optimization strategies. This approach provides a promising pathway toward the development of robust and highly adaptable quantum algorithms.

DOI: 10.5281/zenodo.22195550

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