基于图的量子计算的拓扑结构

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper explores the application of graph-based quantum computing frameworks, focusing on the utilization of graph topology for describing quantum circuit operations and performance optimization. We propose a novel approach to quantum algorithm design, leveraging graph structures to enhance computational efficiency and explore potential advancements in quantum computation. The core mechanism involves constructing quantum circuits as graphs, then utilizing graph topology to guide the design process, thereby improving the overall performance. We investigate the implications of this methodology within the context of quantum algorithms and outline future research directions.

DOI: 10.5281/zenodo.22152667

Related papers

Optimization Algorithms Based on Graph Theory for Quantum Computing

Jincheng Zhang

Quantum computing offers the potential for revolutionary advancements across diverse fields, demanding efficient algorithms and hardware architectures. Traditional optimization methods often overlook the inherent structural properties of quantum circuits, hindering their potential for optimal performance. This paper proposes a novel optimization algorithm based on graph theory, designed to leverage the structural characteristics of quantum circuits to enhance efficiency. The core mechanism involves representing quantum circuits as graphs, utilizing graph properties to guide the optimization process. We explore the application of this approach to optimize quantum circuit parameters, focusing on minimizing circuit depth and improving fidelity. The paper details the algorithm's architecture, the mathematical underpinnings of its optimization strategy, and preliminary results demonstrating its effectiveness in optimizing quantum circuits. The research highlights the potential of graph-based optimization to accelerate the development of practical quantum algorithms.

Aug 31, 20260 citations

拓扑结构与量子算法

Jincheng Zhang

This paper investigates the application of topological structures in quantum algorithms, aiming to enhance their efficiency and reliability. We explore the potential of utilizing topological properties to design novel quantum algorithms that offer significant advantages over traditional approaches. The core mechanism focuses on leveraging topological invariants to guide quantum computation, reducing the need for complex optimization and improving overall performance. The study analyzes various topological concepts and their implications for quantum algorithm design, proposing a new algorithm predicated on these principles. This work presents a conceptual framework for integrating topological analysis into quantum algorithm development, demonstrating the potential of this approach to advance the field. The paper concludes with a discussion of future research directions and the challenges associated with implementing this concept.

Aug 31, 20260 citations

基于非线性拓扑的量子计算的拓扑优化算法

Jincheng Zhang

Quantum computing offers unprecedented computational power, but the design and optimization of quantum circuits often face significant challenges, particularly in the context of complex quantum algorithms. This paper proposes a novel approach to quantum computing, utilizing a modified version of the topological optimization algorithm, to address these challenges. We introduce a new framework that leverages the inherent topological properties of quantum systems to dynamically adjust the structure of quantum circuits, enabling more efficient and robust optimization. The core mechanism focuses on exploiting the non-linear nature of topological spaces to guide the evolution of quantum states, ultimately improving the performance of quantum algorithms. This research explores the potential of this approach to tackle specific problems in quantum information processing and highlights its advantages over existing methods.

Sep 4, 20260 citations

基于自适应量子拓扑的算法设计

Jincheng Zhang

This paper introduces a novel algorithmic framework, termed "Adaptive Quantum Topology" (AQT), designed to optimize quantum computation. The core principle of AQT leverages the unique properties of quantum topology – a mathematical concept describing the interconnectedness of quantum states – to enhance the efficiency of quantum algorithms. The paper details the framework's design, emphasizing its capacity to generate novel quantum circuits and improve overall computational performance. The significance of this work lies in its potential to overcome limitations of traditional approaches, offering a fundamentally different paradigm for quantum algorithm design. This research explores the mathematical foundations of AQT, outlining the key steps involved in generating and optimizing quantum circuits that exhibit enhanced coherence and fidelity. We present a rigorous analysis of the framework's performance with specific examples demonstrating its efficacy in various quantum computation tasks. The paper concludes with a discussion of future research directions and potential applications.

Sep 2, 20260 citations

基于量子拓扑的量子计算

Jincheng Zhang

This paper introduces a novel quantum computing approach based on quantum topology, leveraging its unique properties to design a quantum computation framework optimized for task solving and enhanced stability. Traditional quantum computing primarily focuses on classical computations, and this research explores the potential of quantum topology to deliver more efficient and stable quantum computation. The core mechanism involves constructing a quantum computation framework utilizing quantum topology, followed by an optimization process driven by understanding the inherent characteristics of quantum computation. This work aims to push the boundaries of quantum computing, potentially revealing more effective quantum algorithms and improved performance.

Sep 4, 20260 citations

Topological-Quantum Path Optimization

Jincheng Zhang

This paper investigates the application of topological-quantum path optimization algorithms to enhance quantum computation. Traditional quantum computing relies on classical computers for algorithm design and implementation. We propose a novel approach that leverages the inherent topological properties of quantum systems to guide the optimization of quantum paths, leading to improved efficiency and potentially new quantum algorithms. This research focuses on establishing a framework for optimizing quantum trajectories using topological concepts, aiming to overcome limitations inherent in existing quantum computing methods. The core mechanism involves utilizing topological structures to represent the quantum state and guide the optimization process, ultimately improving the performance of quantum systems.

Sep 3, 20260 citations