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

基于量子纠缠的自适应量子态转移算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations
Publisher

Abstract

Quantum state transfer is a fundamental operation in quantum information processing, enabling the manipulation of quantum states across different systems. Traditional approaches often struggle with the limitations of classical information transfer, particularly in scenarios requiring rapid and efficient transfer of quantum information. This paper introduces a novel quantum state transfer algorithm based on the intrinsic self-correlation of quantum entanglement, aiming to overcome these limitations through a dynamic and predictive approach. The algorithm leverages entangled states to facilitate the instantaneous and controlled transfer of quantum information, significantly enhancing the fidelity and speed of state transfer. We detail the core mechanism, including the use of entangled states for self-adaptation and prediction, and present preliminary results demonstrating its effectiveness. The proposed algorithm offers a promising pathway toward more robust and scalable quantum information transfer protocols.

DOI
10.5281/zenodo.22300011

Related papers

自组织量子态的量子态转移算法

Jincheng Zhang

Quantum state transfer is a crucial process in quantum information processing, enabling the manipulation of quantum states across different platforms. Traditional approaches often struggle with computational complexity and limited transfer efficiency. This paper introduces a novel quantum state transfer algorithm predicated on the principles of self-organized quantum states. We propose a mechanism leveraging the inherent adaptability of these states to facilitate rapid and efficient state transfer, offering a significant advancement over existing methods. The algorithm utilizes self-organization to dynamically adjust the quantum state, thereby optimizing the transfer process. The core claim details the algorithm's ability to achieve faster and more reliable state transfers, including the prediction of transfer pathways. This work explores the potential of this approach to address challenges in quantum information transfer.

•Sep 4, 2026•0 citations

基于自适应的量子态的自适应拓扑变换

Jincheng Zhang

This paper investigates a novel approach to quantum state manipulation leveraging the inherent properties of quantum entanglement. We propose a robust and adaptable quantum state transformation method, termed "Adaptive Topological Transformation" (ATT), that dynamically adjusts the quantum state's topology through the application of entangled correlations. The ATT algorithm aims to enhance quantum information processing and transmission by enabling efficient and flexible transformations of quantum states, overcoming the limitations of traditional optimization techniques. This work introduces a novel mechanism centered around the dynamic manipulation of quantum entanglement, offering a promising pathway to more efficient and versatile quantum operations. The core claim centers on the utilization of entangled correlations to dynamically shape the quantum state's topology, resulting in improved computational and communication efficiency.

•Sep 4, 2026•0 citations

基于自适应拓扑的量子态转移与编码

Jincheng Zhang

This paper investigates the potential of leveraging self-adaptive topology for quantum state transfer and encoding. The core challenge in quantum information processing lies in efficiently transferring and encoding quantum states, often requiring complex and computationally intensive manipulations. Traditional approaches struggle with these challenges due to their reliance on static qubit configurations. We propose a novel framework utilizing self-adaptive topology to dynamically adjust the encoding and manipulation of quantum states, potentially leading to significant improvements in quantum state fidelity and computational efficiency. The proposed method focuses on constructing a robust and adaptable topology that facilitates precise state transfers and encodes, offering a fundamentally different approach to quantum information processing. The paper details the design of a self-adaptive topology, the implementation of a transfer algorithm, and the resulting performance improvements compared to existing methods. Finally, we discuss the potential implications of this research for advancing the capabilities of quantum computing.

•Aug 31, 2026•0 citations

基于自适应的量子态迁移算法

Jincheng Zhang

Quantum state manipulation is a cornerstone of quantum computing, enabling complex computations and novel quantum algorithms. Traditional quantum state transfer protocols, while effective, often rely on predefined parameters and can be inflexible in the face of system dynamics. This paper introduces a novel algorithm, termed "Adaptive Quantum State Migration," designed to dynamically adjust quantum state parameters based on system feedback, thereby enhancing optimization efficiency and performance. The core mechanism leverages a self-adaptive algorithm to continuously refine the quantum state, adapting to changes in the system. This approach overcomes limitations of static protocols, providing a more robust and adaptable solution for quantum state management. We present a detailed analysis of the algorithm's performance and demonstrate its efficacy through illustrative examples. This research focuses on optimizing the transition of quantum states within a quantum system, showcasing its potential for broader applications in quantum information processing.

•Aug 31, 2026•0 citations

Adaptive State Transfer of Multi-Body Quantum Entanglement

Jincheng Zhang

This paper introduces a novel algorithm for adaptive state transfer of multi-body quantum entanglement, aiming to accelerate the transition between different quantum states. The core concept is leveraging the unique properties of quantum entanglement to facilitate rapid and efficient state manipulation. Traditional approaches often rely on static transitions, while this algorithm dynamically adjusts the state to optimize for speed and efficiency. We explore a method that utilizes entanglement as a dynamic pathway for state transformation, achieving significantly enhanced transfer rates compared to existing techniques. The paper details the algorithm's architecture, introduces key mathematical formulations, and provides a preliminary analysis demonstrating its potential for substantial speedup in complex quantum systems.

•Sep 7, 2026•0 citations

基于自适应的微观量子计算算法

Jincheng Zhang

This paper introduces a novel approach to quantum computing based on adaptive quantum state and entanglement manipulation. Traditional quantum algorithms often struggle to accurately simulate complex quantum systems, while adaptive quantum control offers the potential for increased computational efficiency. This work details the development of a new algorithm, termed "Dynamic Quantum Modulation" (DQM), which leverages self-adjusting parameters to dynamically control quantum states and entanglement, facilitating more precise and efficient simulation of quantum systems. We demonstrate the effectiveness of DQM through theoretical analysis and preliminary simulations, highlighting its potential to overcome limitations of existing quantum computing methods. The core mechanism centers around intelligently adjusting quantum states and entanglement to achieve a higher level of simulation fidelity and computational speed.

•Aug 31, 2026•0 citations
Quantum state transfer is a fundamental operation in quantum information processing, enabling the manipulation of quantum states across different systems. Traditional approaches often struggle with the limitations of classical information transfer, particularly in scenarios requiring rapid and efficient transfer of quantum information. This paper introduces a novel quantum state transfer algorithm based on the intrinsic self-correlation of quantum entanglement, aiming to overcome these limitations through a dynamic and predictive approach. The algorithm leverages entangled states to facilitate the instantaneous and controlled transfer of quantum information, significantly enhancing the fidelity and speed of state transfer. We detail the core mechanism, including the use of entangled states for self-adaptation and prediction, and present preliminary results demonstrating its effectiveness. The proposed algorithm offers a promising pathway toward more robust and scalable quantum information transfer protocols.
Quantum state transfer is a crucial process in quantum information processing, enabling the manipulation of quantum states across different platforms. Traditional approaches often struggle with computational complexity and limited transfer efficiency. This paper introduces a novel quantum state transfer algorithm predicated on the principles of self-organized quantum states. We propose a mechanism leveraging the inherent adaptability of these states to facilitate rapid and efficient state transfer, offering a significant advancement over existing methods. The algorithm utilizes self-organization to dynamically adjust the quantum state, thereby optimizing the transfer process. The core claim details the algorithm's ability to achieve faster and more reliable state transfers, including the prediction of transfer pathways. This work explores the potential of this approach to address challenges in quantum information transfer.
This paper investigates a novel approach to quantum state manipulation leveraging the inherent properties of quantum entanglement. We propose a robust and adaptable quantum state transformation method, termed "Adaptive Topological Transformation" (ATT), that dynamically adjusts the quantum state's topology through the application of entangled correlations. The ATT algorithm aims to enhance quantum information processing and transmission by enabling efficient and flexible transformations of quantum states, overcoming the limitations of traditional optimization techniques. This work introduces a novel mechanism centered around the dynamic manipulation of quantum entanglement, offering a promising pathway to more efficient and versatile quantum operations. The core claim centers on the utilization of entangled correlations to dynamically shape the quantum state's topology, resulting in improved computational and communication efficiency.
This paper investigates the potential of leveraging self-adaptive topology for quantum state transfer and encoding. The core challenge in quantum information processing lies in efficiently transferring and encoding quantum states, often requiring complex and computationally intensive manipulations. Traditional approaches struggle with these challenges due to their reliance on static qubit configurations. We propose a novel framework utilizing self-adaptive topology to dynamically adjust the encoding and manipulation of quantum states, potentially leading to significant improvements in quantum state fidelity and computational efficiency. The proposed method focuses on constructing a robust and adaptable topology that facilitates precise state transfers and encodes, offering a fundamentally different approach to quantum information processing. The paper details the design of a self-adaptive topology, the implementation of a transfer algorithm, and the resulting performance improvements compared to existing methods. Finally, we discuss the potential implications of this research for advancing the capabilities of quantum computing.
Quantum state manipulation is a cornerstone of quantum computing, enabling complex computations and novel quantum algorithms. Traditional quantum state transfer protocols, while effective, often rely on predefined parameters and can be inflexible in the face of system dynamics. This paper introduces a novel algorithm, termed "Adaptive Quantum State Migration," designed to dynamically adjust quantum state parameters based on system feedback, thereby enhancing optimization efficiency and performance. The core mechanism leverages a self-adaptive algorithm to continuously refine the quantum state, adapting to changes in the system. This approach overcomes limitations of static protocols, providing a more robust and adaptable solution for quantum state management. We present a detailed analysis of the algorithm's performance and demonstrate its efficacy through illustrative examples. This research focuses on optimizing the transition of quantum states within a quantum system, showcasing its potential for broader applications in quantum information processing.
This paper introduces a novel algorithm for adaptive state transfer of multi-body quantum entanglement, aiming to accelerate the transition between different quantum states. The core concept is leveraging the unique properties of quantum entanglement to facilitate rapid and efficient state manipulation. Traditional approaches often rely on static transitions, while this algorithm dynamically adjusts the state to optimize for speed and efficiency. We explore a method that utilizes entanglement as a dynamic pathway for state transformation, achieving significantly enhanced transfer rates compared to existing techniques. The paper details the algorithm's architecture, introduces key mathematical formulations, and provides a preliminary analysis demonstrating its potential for substantial speedup in complex quantum systems.
This paper introduces a novel approach to quantum computing based on adaptive quantum state and entanglement manipulation. Traditional quantum algorithms often struggle to accurately simulate complex quantum systems, while adaptive quantum control offers the potential for increased computational efficiency. This work details the development of a new algorithm, termed "Dynamic Quantum Modulation" (DQM), which leverages self-adjusting parameters to dynamically control quantum states and entanglement, facilitating more precise and efficient simulation of quantum systems. We demonstrate the effectiveness of DQM through theoretical analysis and preliminary simulations, highlighting its potential to overcome limitations of existing quantum computing methods. The core mechanism centers around intelligently adjusting quantum states and entanglement to achieve a higher level of simulation fidelity and computational speed.