Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

拓扑信息论的量子态分解与演化

Jincheng Zhang

Published Sep 5, 2026• 0 citations
Publisher

Abstract

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.

DOI
10.5281/zenodo.22328059

Related papers

基于拓扑的量子态分解与计算

Jincheng Zhang

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.

•Aug 31, 2026•0 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, 2026•0 citations

基于量子拓扑的量子态生成

Jincheng Zhang

This paper introduces a novel quantum state generation algorithm based on quantum topology. Traditional quantum state generation methods rely on classical computation, while our approach leverages the unique properties of quantum topology to generate complex quantum states with precise control and simulation capabilities. We detail the algorithm's core mechanism, including the construction of a topological structure and the subsequent quantum state evolution. The potential implications of this algorithm for quantum information processing and quantum simulation are significant, offering a pathway towards more efficient and versatile quantum state manipulation.

•Sep 5, 2026•0 citations

拓扑信息论的量子态转移与操控

Jincheng Zhang

The pursuit of quantum computation has spurred significant advancements in quantum information theory, particularly in the realm of quantum state transfer and manipulation. Traditional approaches often rely on precise pulse control, limiting the potential for highly efficient and robust quantum operations. This paper introduces a novel framework based on topological information theory, offering a fundamentally different approach to manipulating quantum states. We propose a system where the state transfer and control are governed by topological structures, enabling precise and efficient operations through dynamic adjustments. The core mechanism involves defining transfer and manipulation rules based on the structure of the underlying topology, achieving improvements in quantum computation's efficiency. This work establishes a new paradigm for quantum state manipulation, leveraging the power of topological principles to enhance the capabilities of quantum systems.

•Aug 31, 2026•0 citations

Dynamic Topology-Based Quantum State Decomposition

Jincheng Zhang

Quantum state decomposition is a crucial challenge in quantum computing, enabling efficient manipulation and computation of quantum states. This paper introduces a novel dynamic topology-based quantum state decomposition method that leverages the inherent structure of quantum systems to achieve high accuracy and computational efficiency. We propose a novel algorithm that dynamically adjusts the quantum state based on topological principles, allowing for precise state manipulation and improved quantum processing. The core mechanism involves constructing a dynamically evolving decomposition topology, which significantly enhances the fidelity of state operations. This approach offers a significant advancement over traditional methods and addresses key limitations in quantum state manipulation.

•Aug 31, 2026•0 citations

基于自适应拓扑网络的量子态预测算法

Jincheng Zhang

This paper presents a novel quantum state prediction algorithm based on an adaptive topology network. Traditional quantum state prediction methods often rely on static models, limiting their ability to accurately predict quantum state evolution. This algorithm leverages the dynamic nature of topology to achieve more efficient and adaptive state optimization. The core mechanism involves adjusting the topology structure dynamically, enabling a more nuanced and precise prediction of quantum states. We demonstrate the algorithm's effectiveness through theoretical analysis and simulation, showcasing improvements in prediction accuracy and state optimization compared to existing approaches. The resulting system offers a significant step towards enhanced quantum control and manipulation.

•Aug 31, 2026•0 citations
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.
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.
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.
This paper introduces a novel quantum state generation algorithm based on quantum topology. Traditional quantum state generation methods rely on classical computation, while our approach leverages the unique properties of quantum topology to generate complex quantum states with precise control and simulation capabilities. We detail the algorithm's core mechanism, including the construction of a topological structure and the subsequent quantum state evolution. The potential implications of this algorithm for quantum information processing and quantum simulation are significant, offering a pathway towards more efficient and versatile quantum state manipulation.
The pursuit of quantum computation has spurred significant advancements in quantum information theory, particularly in the realm of quantum state transfer and manipulation. Traditional approaches often rely on precise pulse control, limiting the potential for highly efficient and robust quantum operations. This paper introduces a novel framework based on topological information theory, offering a fundamentally different approach to manipulating quantum states. We propose a system where the state transfer and control are governed by topological structures, enabling precise and efficient operations through dynamic adjustments. The core mechanism involves defining transfer and manipulation rules based on the structure of the underlying topology, achieving improvements in quantum computation's efficiency. This work establishes a new paradigm for quantum state manipulation, leveraging the power of topological principles to enhance the capabilities of quantum systems.
Quantum state decomposition is a crucial challenge in quantum computing, enabling efficient manipulation and computation of quantum states. This paper introduces a novel dynamic topology-based quantum state decomposition method that leverages the inherent structure of quantum systems to achieve high accuracy and computational efficiency. We propose a novel algorithm that dynamically adjusts the quantum state based on topological principles, allowing for precise state manipulation and improved quantum processing. The core mechanism involves constructing a dynamically evolving decomposition topology, which significantly enhances the fidelity of state operations. This approach offers a significant advancement over traditional methods and addresses key limitations in quantum state manipulation.
This paper presents a novel quantum state prediction algorithm based on an adaptive topology network. Traditional quantum state prediction methods often rely on static models, limiting their ability to accurately predict quantum state evolution. This algorithm leverages the dynamic nature of topology to achieve more efficient and adaptive state optimization. The core mechanism involves adjusting the topology structure dynamically, enabling a more nuanced and precise prediction of quantum states. We demonstrate the algorithm's effectiveness through theoretical analysis and simulation, showcasing improvements in prediction accuracy and state optimization compared to existing approaches. The resulting system offers a significant step towards enhanced quantum control and manipulation.