基于图的逻辑推理的量子计算验证

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper investigates the potential of utilizing graph-based logical reasoning algorithms to validate quantum computation algorithms, offering a novel approach to quantum algorithm verification that surpasses traditional simulation-based methods. We propose a framework where the core mechanism involves constructing a graph representing the algorithm's state space and applying logical inference to this graph. The goal is to dynamically test the algorithm's behavior and identify potential errors through rigorous logical analysis. The paper details the design of a graph-based verification protocol, explores the benefits of this approach, and discusses preliminary results demonstrating improved efficiency and insight into quantum algorithm robustness. We conclude that this technique represents a significant advancement in quantum algorithm verification, offering a pathway to more reliable and efficient quantum computation.

DOI: 10.5281/zenodo.22267381

Related papers

基于图的逻辑推理的量子计算

Jincheng Zhang

This paper investigates the potential of leveraging graph-based logic reasoning and quantum computing to tackle complex problems in fields such as drug discovery and cryptography. The core concept is to integrate graph structures with quantum computation to facilitate efficient and robust logical inference. We explore a novel framework that utilizes quantum algorithms to enhance the process of reasoning through complex logical structures represented by graphs. The paper discusses the challenges and opportunities presented by this approach, highlighting its potential to overcome limitations of traditional methods. The investigation delves into the design of quantum algorithms tailored to specific logical inference tasks, considering both the graph representation and quantum computation's inherent advantages. The paper concludes with a preliminary assessment of the feasibility and impact of this integrated approach, suggesting avenues for further research and development.

Aug 31, 20260 citations

自适应量子拓扑的量子算法验证

Jincheng Zhang

This paper explores the application of self-adaptive quantum topology to quantum algorithm verification. Traditional algorithm validation relies on classical testing methods, while this approach leverages the unique properties of quantum topology to enhance verification accuracy. We propose a novel quantum algorithm that dynamically adjusts the quantum state to test the correctness of a given quantum algorithm, mitigating potential errors and improving the reliability of quantum computations. The core mechanism centers around utilizing topological invariants to establish a rigorous and efficient verification process. This research aims to provide a fundamentally new method for validating quantum algorithms, offering a robust and potentially scalable solution to verification challenges.

Sep 3, 20260 citations

基于量子纠缠的算法验证框架 (QAF)

Jincheng Zhang

This paper introduces a novel algorithm validation framework, termed Quantum Entanglement Verification (QAF), designed to rigorously verify quantum algorithms' correctness and robustness. Traditional verification methods often rely on computationally intensive tasks, limiting their applicability to relatively small-scale quantum systems. QAF leverages the unique properties of quantum entanglement to provide a fundamentally different approach, offering a potentially more efficient and reliable method for assessing the validity of quantum computations. The framework focuses on establishing a measurable relationship between the algorithm's output and the entangled state of the qubits involved, minimizing reliance on traditional error analysis. This paper details the core mechanics of QAF, including the design of a specific measurement protocol and the associated mathematical formulation, and discusses its potential impact on the field of quantum algorithm verification. We demonstrate the framework's efficacy through theoretical analysis and preliminary experimental validation, highlighting its advantages in terms of accuracy and scalability.

Sep 4, 20260 citations

基于量子隐形态的图灵机验证 - 证明复杂系统安全性的理论框架

Jincheng Zhang

This paper introduces a novel framework for quantum-enhanced graph theory verification, specifically designed for validating complex systems. The core idea is to leverage quantum superposition and entanglement to simulate the behavior of these systems and utilize quantum algorithms for verification purposes. This approach aims to significantly improve the efficiency and accuracy of verification, offering a potential breakthrough for security analysis across diverse domains, including protein structure, chemical reactions, and more. The paper details the proposed mechanism, discusses the benefits and challenges associated with this quantum approach, and concludes with a preliminary assessment of its theoretical soundness and practical implications. We demonstrate a conceptual model and outline a pathway toward further exploration and refinement of this framework.

Aug 31, 20260 citations

基于动态拓扑的量子算法验证框架

Jincheng Zhang

Quantum algorithms, due to their inherent fragility and susceptibility to errors, require rigorous verification. Traditional verification methods often rely on exhaustive testing, which is computationally expensive and impractical for complex quantum systems. This paper introduces a novel framework, "Dynamic Topological Verification," (DTV) that leverages the principles of dynamic topology to validate quantum algorithms. DTV dynamically constructs and analyzes topological structures within the quantum circuit, ensuring the algorithm's correctness through self-consistent and adaptive adjustments. This approach offers enhanced reliability and robustness, surpassing conventional verification techniques. The framework's core mechanism involves the construction of a topological graph representing the quantum circuit, followed by a process of iterative refinement and verification based on these graphs. We demonstrate the effectiveness of DTV through the analysis of a simplified quantum algorithm, showcasing its ability to detect subtle errors and improve the algorithm's performance.

Sep 7, 20260 citations

基于自适应量子拓扑的算法验证

Jincheng Zhang

This paper introduces a novel algorithm validation framework based on adaptive quantum topology. Traditional algorithm verification relies on static validation methods, which often suffer from limitations in scalability and adaptability. Our approach leverages the dynamic nature of quantum topology to dynamically adjust the validation criteria, enhancing verification efficiency and enabling the discovery of novel algorithm patterns. We detail the framework's design, explain the underlying mathematical principles, and provide a preliminary validation example demonstrating the framework's capabilities. The core mechanism centers around constructing a "quantum topology graph" representing the algorithm's state and iteratively updating this graph to ensure the algorithm's properties are consistently satisfied. This framework offers a significant advancement over existing methods by providing a more flexible and robust validation process.

Sep 4, 20260 citations