Nonlinear Topological Structures for Quantum Algorithm Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum algorithm optimization is a significant challenge in the field of quantum computing. Traditional optimization methods often focus on maximizing computational throughput, while the inherent complexity of quantum systems necessitates a novel approach. This paper introduces a novel framework, termed "Nonlinear Topological Structures for Quantum Algorithm Optimization," which leverages the unique properties of non-linear topological structures to guide the optimization process. The core mechanism involves mapping the quantum algorithm's parameters to a topological space, allowing for the exploration of diverse parameter configurations through a process of 'topological folding' and 'pathfinding.' We demonstrate the effectiveness of this framework through a series of simulations and analysis, showcasing significant improvements in algorithm efficiency and stability compared to existing methods. The study highlights the potential of utilizing non-linear topology to address challenges in quantum algorithm design and optimization.

DOI: 10.5281/zenodo.22289526

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