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基于量子拓扑的自适应量子势评估

Jincheng Zhang

Published Sep 4, 2026• 0 citations
Publisher

Abstract

This paper introduces a novel quantum state evaluation framework based on topological principles. Traditional quantum state evaluation methods often rely on static adjustments to the quantum potential, limiting accuracy and robustness. We propose a dynamic adjustment mechanism that leverages the inherent topological properties of the quantum system to optimize the evaluation process. This approach offers improved accuracy and adaptability compared to static methods. We demonstrate the effectiveness of this framework through simulations and theoretical analysis, showcasing its potential for enhancing quantum state assessment across various quantum systems.

DOI
10.5281/zenodo.22295275

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This paper introduces a novel quantum state evaluation framework based on topological principles. Traditional quantum state evaluation methods often rely on static adjustments to the quantum potential, limiting accuracy and robustness. We propose a dynamic adjustment mechanism that leverages the inherent topological properties of the quantum system to optimize the evaluation process. This approach offers improved accuracy and adaptability compared to static methods. We demonstrate the effectiveness of this framework through simulations and theoretical analysis, showcasing its potential for enhancing quantum state assessment across various quantum systems.
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This paper explores the application of quantum spin dynamics to the assessment of topological structures. Traditional methods often rely on static analysis, which can be limited in capturing the intricate changes within a topological system. We propose a novel dynamic quantum spin algorithm that dynamically adjusts quantum spin parameters to evaluate the evolution of topological structures. This approach offers the potential for significantly improved accuracy and efficiency in assessing the robustness and dynamic behavior of topological materials. The core mechanism involves a continuous, iterative adjustment of the quantum spin states, driven by a predefined set of parameters, to mimic the iterative processes involved in topological phase transitions. We demonstrate the effectiveness of this method through simulations and preliminary experiments, showcasing its ability to accurately characterize the stability and responsiveness of various topological systems. The results indicate a substantial improvement in the assessment of topological structure dynamics compared to traditional approaches.
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Quantum computing is a rapidly advancing field with the potential to revolutionize various industries through its unique computational capabilities. However, achieving high-performance quantum algorithms requires careful optimization of quantum circuits, particularly the design of quantum state vectors, which is currently a significant bottleneck. This paper introduces a novel approach to quantum state vector optimization leveraging the principles of quantum topology. We propose a method that dynamically adjusts the quantum state by exploiting the inherent topological properties of the quantum system, resulting in improved accuracy and efficiency in various quantum computing tasks. The core mechanism centers around constructing and manipulating quantum states through a carefully orchestrated topological transformation, offering a fundamentally different perspective on optimization compared to existing methods. This work demonstrates the effectiveness of this approach through theoretical analysis and preliminary experimental validation, showcasing its potential to significantly enhance quantum computation.