基于自适应量子态的拓扑优化算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on dynamically adjusted quantum states, offering a fundamentally different approach to solving complex optimization problems. Traditional optimization methods often rely on static parameters, limiting their applicability to relatively simple problems. This paper proposes a quantum-enhanced algorithm that dynamically modifies the quantum state of the system, enabling the exploration of complex topological structures and facilitating precise control over these structures. The core mechanism leverages the inherent properties of quantum mechanics – superposition, entanglement, and interference – to achieve a level of optimization previously unattainable through classical methods. This algorithm demonstrates promising results in optimizing a specific topological structure, showcasing its potential for broader applicability across diverse fields.

DOI: 10.5281/zenodo.22292637

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