Dynamic Quantum Algorithm Topology Analysis

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of dynamic quantum algorithms to adapt to input data's topological structure, leading to enhanced computational efficiency and precision. We propose a novel algorithm that dynamically adjusts quantum algorithm parameters based on the input, optimizing the algorithm's performance. The core mechanism centers around a feedback loop that continuously refines the quantum state to achieve optimal results. This approach contrasts sharply with traditional quantum algorithms, which typically rely on pre-defined parameters, offering a significant advancement in adaptability and control. The study delves into the theoretical underpinnings of this dynamic adjustment, examining its impact on algorithm convergence and accuracy. We provide a detailed analysis of the algorithm's design, showcasing its potential for solving complex problems with improved computational throughput.

DOI: 10.5281/zenodo.22195369

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