基于拓扑的量子态分解与计算

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum state decomposition method based on topological properties. Traditional approaches often rely on complex quantum circuits, while topological methods offer a more intrinsic and physical description. We propose a method that leverages topological structures to efficiently decompose quantum states and facilitate quantum state computation and evolution. The core mechanism involves constructing and manipulating topological structures to represent the quantum state, enabling optimized calculations and manipulations. The advantages of this approach include improved efficiency, reduced complexity, and a deeper understanding of quantum information. We demonstrate the effectiveness of this method through theoretical analysis and preliminary numerical simulations.

DOI: 10.5281/zenodo.22201903

Related papers

拓扑信息论的量子态分解与演化

Jincheng Zhang

This paper introduces a novel quantum state decomposition and evolution algorithm based on topological information theory. Traditional quantum state decomposition methods often rely on classical computation, while this approach leverages the unique properties of topology to achieve precise decomposition and evolution of quantum states, leading to enhanced computational efficiency. The core mechanism involves constructing a topological structure that governs the evolution of the quantum state, enabling efficient and controlled manipulation of its properties. This work demonstrates the effectiveness of this algorithm through theoretical analysis and preliminary experimental results, offering a promising alternative for quantum computation.

Sep 5, 20260 citations

自适应拓扑的量子态分解

Jincheng Zhang

This paper introduces a novel quantum state decomposition algorithm based on adaptive topology, offering a promising approach to optimization and control in quantum computing. Traditional state decomposition methods often rely on manual design, lacking the ability to learn from data. Our framework leverages the inherent topological structure of quantum states to efficiently decompose them, enabling enhanced optimization and control capabilities. This work presents a theoretical analysis and preliminary implementation demonstrating the algorithm's effectiveness and potential for significant advancements within the field. The core mechanism involves manipulating the topology of a quantum state through a series of transformations, ultimately leading to a more structured and manageable representation.

Sep 4, 20260 citations

基于拓扑的量子态模拟器

Jincheng Zhang

This paper introduces a novel quantum state simulator based on topological structures, offering a fundamentally different approach compared to traditional methods. We detail the design and implementation of a quantum state simulator utilizing topological phases to dynamically explore and predict quantum state evolution. The core mechanism involves constructing a topological framework that guides the simulation process, enabling efficient analysis of complex quantum states. We present preliminary results demonstrating the simulator's ability to accurately predict quantum state behavior and provide theoretical insights into quantum computation. The paper highlights the advantages of this approach in terms of computational efficiency and the potential for deeper understanding of quantum phenomena.

Sep 5, 20260 citations

基于量子拓扑的自适应量子计算的拓扑结构分析

Jincheng Zhang

This paper explores the application of quantum topology for adaptive quantum computation, proposing a novel method for structure analysis that leverages the inherent topological properties of quantum systems to optimize computation. Traditional approaches often rely on manual design, limiting flexibility and efficiency. This work introduces a framework wherein quantum topology is employed to guide the optimization of complex quantum circuits, resulting in improved computational performance. We present a preliminary algorithm demonstrating the potential of this approach, highlighting its advantages over conventional methods. The core mechanism centers on identifying and manipulating topological landscapes to enhance quantum circuit performance.

Sep 3, 20260 citations

基于自适应拓扑的量子态量子化

Jincheng Zhang

This paper introduces a novel quantum state quantumization method based on adaptive topology. Traditional quantum computing relies on complex quantum circuits, while topology offers a more intrinsic and physical description. We propose a new approach that leverages adaptive algorithms to dynamically adjust the encoding and manipulation of quantum states, enabling precise control and quantum state quantization. The core mechanism centers around utilizing topological structures to guide and refine the quantum state, ultimately improving the fidelity and controllability of quantum computations. This work addresses a fundamental challenge in quantum information processing by providing a fundamentally different approach to state representation and manipulation.

Aug 31, 20260 citations

基于量子纠缠的拓扑信息理论

Jincheng Zhang

This paper introduces a novel framework for analyzing and manipulating topological information, leveraging the unique properties of quantum entanglement. We propose a theoretical model based on entanglement that allows for the calculation and analysis of topological structures with enhanced computational efficiency compared to traditional methods. The core mechanism involves establishing a quantum state to represent topological information, utilizing entanglement to facilitate calculations and providing a foundation for the design of robust topological data structures. The study explores the potential of this approach to revolutionize the field of topological information theory.

Aug 31, 20260 citations