基于动态拓扑的量子计算算法

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel quantum computing algorithm based on dynamic topology, offering a fundamentally different approach to optimization and computation compared to traditional methods. The algorithm leverages the inherent flexibility of topological structures to dynamically adjust quantum states and perform complex calculations. We detail the core mechanism, outlining how the algorithm leverages topological properties to enhance computational efficiency and explore new quantum solutions. The paper presents a conceptual framework demonstrating the potential of this approach, while highlighting key design choices and preliminary experimental results. The core claim emphasizes the algorithm's ability to adapt to quantum systems and enable novel quantum computations.

DOI: 10.5281/zenodo.22330299

Related papers

基于自适应的量子计算的拓扑优化算法

Jincheng Zhang

This paper presents a novel quantum computing algorithm for topology optimization, leveraging the inherent properties of quantum computation to dynamically adjust the structure of a given topology. Traditional topology optimization methods often rely on static, pre-defined structures, limiting their adaptability to complex, dynamic environments. Our proposed algorithm utilizes quantum superposition and entanglement to explore multiple solution spaces simultaneously, resulting in improved efficiency and the ability to find more optimal solutions. We demonstrate the effectiveness of this approach through simulations and preliminary experimental results. The core mechanism centers around a quantum-enhanced iterative adjustment of a topological structure, allowing the algorithm to efficiently explore a vast solution space and identify optimal configurations. We highlight the advantages of this approach, including robustness to noise and the potential for discovering novel topological structures.

Sep 6, 20260 citations

基于自适应量子计算的拓扑优化算法

Jincheng Zhang

This paper introduces a novel quantum optimization algorithm, termed "Adaptive Topological Optimization," designed to enhance the performance of quantum computations. Traditional optimization methods often struggle with the inherent complexity of quantum systems, necessitating a shift towards quantum-specific approaches. This research focuses on leveraging the unique properties of quantum mechanics – particularly the topological nature of quantum states – to guide optimization processes, offering a potential paradigm shift in quantum algorithm design. The core of this algorithm utilizes a dynamically adjusted quantum state to explore the solution space more efficiently and identify optimal solutions with superior performance. We demonstrate the effectiveness of this approach through a series of simulations and preliminary results, highlighting its potential to significantly improve the efficiency and scalability of quantum computations. The paper concludes with a discussion of the algorithm's underlying principles, its potential applications, and future research directions.

Sep 2, 20260 citations

Adaptive Topology Transformations for Quantum Computing

Jincheng Zhang

This paper introduces a novel adaptive topology transformation algorithm designed for quantum computing, enabling dynamic manipulation of complex topological structures. Traditional topology transformations rely on classical computational methods, while this approach leverages quantum computing's unique properties to achieve more efficient topological optimization. The core mechanism involves quantum state manipulation to induce desired topological changes, offering a fundamentally different approach to topology within the quantum realm. The paper details the algorithm's architecture, key quantum operations, and potential applications, emphasizing its potential to significantly enhance quantum algorithms and computational capabilities.

Aug 29, 20260 citations

基于自适应拓扑结构的量子计算的优化算法

Jincheng Zhang

Quantum computing offers the potential for exponentially faster computation compared to classical computing, but realizing this potential requires significant advancements in algorithm design. This paper explores a novel optimization algorithm for quantum computation, leveraging the principles of adaptive topology to enhance the efficiency of quantum state manipulation. We introduce a dynamically adjusted topology structure, which allows for optimization of qubit placement and entanglement, ultimately leading to improved quantum computational performance. The core mechanism centers around a self-adaptive algorithm that continuously refines the quantum state to achieve optimal results. This approach contrasts with traditional static optimization methods, offering a promising path towards unlocking the full capabilities of quantum systems. The paper details the algorithm's design, analysis, and preliminary experimental results, demonstrating its potential for enhancing quantum computation.

Aug 31, 20260 citations

基于量子拓扑的量子计算的自适应拓扑调整

Jincheng Zhang

Quantum computing offers unprecedented computational power, but current challenges lie in achieving reliable and precise results, particularly in complex calculations. This paper investigates a novel approach to quantum computation utilizing the principles of quantum topology – specifically, a dynamically adjustable topology shift. We propose a method based on quantum system evolution and dynamic adjustment of quantum topology, designed to enhance the accuracy of quantum computations by adapting the underlying structure during the computation. The core mechanism leverages the inherent properties of quantum topology to dynamically tailor the system's state, thereby enabling a more precise and efficient solution. This research explores the potential of such a technique to overcome limitations of traditional quantum algorithms, offering a promising pathway towards advancing the field of quantum computing.

Sep 7, 20260 citations

基于自适应拓扑的量子计算算法优化

Jincheng Zhang

Quantum computing, leveraging the unique properties of quantum systems, offers the potential for unprecedented computational power. However, the development of efficient quantum algorithms is often hindered by the inherent complexity of quantum systems and the challenges of optimization. This paper introduces a novel quantum algorithm optimization method based on adaptive topology, designed to improve the performance of existing quantum algorithms. The core mechanism utilizes the self-adaptative nature of quantum spin states to dynamically adjust quantum parameters and improve the fidelity of quantum computations. We present a theoretical framework and preliminary experimental results demonstrating the effectiveness of this approach in optimizing a specific quantum circuit. The proposed method offers a promising path towards more efficient and reliable quantum computations. The core claim of the paper is that this adaptive topology-based algorithm significantly enhances the performance of quantum algorithms compared to traditional optimization techniques.

Aug 31, 20260 citations