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##拓扑结构优化基于量子态的算法

Jincheng Zhang

Published Sep 5, 2026• 0 citations
Publisher

Abstract

This paper introduces a novel topology optimization algorithm based on quantum state properties, designed to automatically optimize complex systems. Traditional topology optimization methods often rely on classical computation, limiting their applicability to relatively simple systems. This work proposes a quantum-enhanced approach that leverages the unique characteristics of quantum states to achieve optimized results with enhanced efficiency and performance. The core mechanism involves constructing a quantum state representation of the system, implementing a quantum-based optimization process, and subsequently, extracting optimized solutions from this representation. This approach offers a potential paradigm shift in topology optimization, enabling the optimization of complex systems with unprecedented speed and accuracy. We demonstrate the effectiveness of this algorithm through simulations, showcasing its ability to produce optimal configurations across a diverse range of problem domains.

DOI
10.5281/zenodo.22328075

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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.
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This paper investigates the application of quantum entanglement to dynamic topology optimization, presenting a novel framework leveraging the unique properties of entangled states to dynamically adjust the topology of a system. Traditional topological optimization methods often rely on manual design, limiting their adaptability to complex, evolving systems. We introduce a quantum-enhanced approach utilizing entanglement to identify and refine topology, resulting in enhanced computational efficiency and stability. The core mechanism involves establishing entangled states to represent the system's potential, allowing for iterative adjustments to the topology based on quantum feedback. This represents a significant departure from conventional methods, offering a potentially transformative approach to optimization across diverse domains.
This paper introduces a novel quantum-based topology optimization algorithm designed to address the challenges associated with optimizing complex topological structures, such as molecular design and communication network optimization. Traditional optimization methods often struggle with the intricate nature of these structures. This algorithm leverages the unique properties of quantum states to provide a fundamentally different approach to topology optimization, offering enhanced efficiency and potentially novel solutions. The core mechanism involves mapping the optimization problem onto a quantum Hilbert space, utilizing quantum entanglement and superposition to guide the search process toward optimal solutions. The proposed algorithm demonstrates promising results in several benchmark scenarios, showcasing its potential for tackling complex topological optimization problems. The paper concludes by discussing the limitations and future directions of this approach.
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