Self-Adaptive Quantum State Topology Search

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive quantum state topology search method. Traditional quantum search algorithms often rely on static parameter settings, limiting their efficiency and accuracy. We propose a framework that dynamically adjusts the quantum state's topology to optimize search performance. This approach leverages the unique properties of topology to guide the search process, resulting in improved efficiency and precision. The core mechanism involves adjusting the quantum state's structure in real-time, creating a dynamic search space. This allows the system to explore the search space more effectively, minimizing the need for exhaustive search. This work presents a fundamentally new approach to quantum search, offering the potential for significant advancements in the field.

DOI: 10.5281/zenodo.22295254

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