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Topological Quantum Entanglement Dynamic Topology Optimization

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, presents unique challenges for optimization and control. Traditional methods often struggle with the inherent complexity of entangled states, limiting their practical application. This paper introduces a novel dynamic topology optimization algorithm specifically designed to address this challenge by dynamically adjusting the topology of entangled states. We propose a framework that iteratively refines the entanglement's structure based on a feedback loop, leveraging quantum properties to enhance entanglement strength and robustness. The algorithm's core mechanism centers on a quantum state transformation process, achieving a significant improvement in entanglement fidelity and utility compared to static optimization techniques. This research explores the potential of this approach to unlock new opportunities in quantum information processing and quantum communication.

DOI
10.5281/zenodo.22264295

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Quantum entanglement, a cornerstone of quantum mechanics, presents a unique challenge for information processing and communication. While the phenomenon itself is well-established, the practical application of entanglement often necessitates efficient and stable protocols. This paper explores a novel approach to quantum entanglement optimization, utilizing adaptive topological structures to dynamically adjust the entanglement's structure. We propose a new algorithm, dubbed "Adaptive Topological Optimization," which leverages a self-organized network of topological defects to enhance entanglement fidelity and robustness. This method offers a pathway toward more efficient and stable entanglement generation and manipulation. The core mechanism involves constructing and manipulating a dynamic network of topological defects, which in turn influence the entanglement's properties. The paper details the algorithm's architecture, demonstrates its effectiveness through theoretical analysis and preliminary experimental validation, and provides insights into potential future research directions.
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