Fidelity-Guaranteed Entanglement Routing in Quantum Networks

Li, Jian; Wang, Mingjun; Xue, Kaiping; Li, Ruidong; Yu, Nenghai; Sun, Qibin; Lu, Jun

doi:10.1109/tcomm.2022.3200115

Cited by 40 publications

(8 citation statements)

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“…In [35] the authors considers links with purification and a minimum constraint on the end-to-end fidelity but it does not look at the problem as a multi-objective optimization problem and therefore the found paths are sub-optimal in respect to the bi-dimensional framing of the problem.…”

Section: A Quantum Networkmentioning

confidence: 99%

“…One may look at the network models as being an advance generation model (where entanglement pre-exists before routing takes place) and on-demand generation model (where entanglement is created after routing) [35], [36]. In this work we deal with an advance generation model, where there is a decoupling between the physical layer and the network layer that makes the routing decision, based on the information it has about the link layer.…”

Section: A Quantum Networkmentioning

confidence: 99%

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Shortest Path Finding in Quantum Networks With Quasi-Linear Complexity

et al. 2023

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A fully-quantum network implies the creation of quantum entanglement between a given source node and some other destination node, with a number of quantum repeaters in between. This paper tackles the problem of quantum entanglement distribution by solving the routing problem over an infrastructure based on quantum repeaters and with a finite number of pairs of entangled qubits available in each link. The network model considers that link purification is available such that a nested purification protocol can be applied at each link to generate entangled qubits with higher fidelity than the original ones. A low-complexity multiobjective routing algorithm to find the shortest path between any two given nodes is proposed and assessed for random networks, using a fairly general path extension mechanism that can fit a large family of particular technological requirements. Different types of quantum protocols require different levels of fidelity for the entangled qubit pairs. For that reason, the proposed algorithm identifies the shortest path between two nodes that assures an end-to-end fidelity above a specified threshold. The minimum requirements for the end-toend entanglement fidelity depend on the whole extension of the paths, and cannot be looked at as a local property of each link. Moreover, one needs to keep track not only of the shortest path, but also of longer paths holding more entangled qubits than the shorter paths in order to satisfy the fidelity criterion. Thus, standard single parameter shortest-path algorithms do not necessarily converge to the optimal solution. The problem of finding the best path in a network subject to multiple criteria (known as multi-objective routing) is, in general, an NP-hard problem due to the rapid growth of the number of stored paths. This work proposes a metric that identifies and discards paths that are objectively worse than others. By doing so, the time complexity of the proposed algorithm scales near-to-linearly with respect to the number of nodes in the network, showing that the shortest-path problem in quantum networks can be solved with a complexity very close to the one of the classical counterparts. That is analytically proved for the case where all the links of a path have the same fidelity (homogeneous model). The algorithm is also adapted to a particular type of path extension, where different links along a path can be purified to different degrees, asserting its flexibility and near-to-linearity even when heterogeneous fidelities along the sections of a path are considered.INDEX TERMS Quantum networks, quantum repeaters, path-finding algorithm, end-to-end fidelity, multiobjective routing.The associate editor coordinating the review of this manuscript and approving it for publication was Bijoy Chand Chatterjee .

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Section: A Quantum Networkmentioning

confidence: 99%

Section: A Quantum Networkmentioning

confidence: 99%

Shortest Path Finding in Quantum Networks With Quasi-Linear Complexity

et al. 2023

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“…3) Entangled Pairs: The exchange of information between two quantum nodes can be achieved through entanglement swapping of entangled pairs [9], which are pairs of qubits that are quantum-mechanically linked, such that the state of one (regardless of the distance separating them) instantaneously influences the state of the other. When entanglement connections span long distances, the fidelity of entangled pairs may degrade due to imperfect measurements on quantum repeaters during entanglement swapping operations.…”

Section: Quantum Resourcesmentioning

confidence: 99%

“…Therefore, the total number of qubits required would be 2n-k+1 qubits. In the experiment, each computing node executes the quantum autoencoders to compress information from [6,9] qubits to [3,5] qubits. In the networks, the number of mobile nodes is set to 10, the number of edge nodes is set to 5, and there is one cloud node.…”

Section: Use Case: Multi-agent Reinforcement Learning-based Resource ...mentioning

confidence: 99%

Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

Niyato

Yang

et al. 2023

IEEE J. Sel. Top. Signal Process.

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Quantum computing networks enable scalable collaboration and secure information exchange among multiple classical and quantum computing nodes while executing large-scale generative AI computation tasks and advanced quantum algorithms. Quantum computing networks overcome limitations such as the number of qubits and coherence time of entangled pairs and offer advantages for generative AI infrastructure, including enhanced noise reduction through distributed processing and improved scalability by connecting multiple quantum devices. However, efficient resource allocation in quantum computing networks is a critical challenge due to factors including qubit variability and network complexity. In this article, we propose an intelligent resource allocation framework for quantum computing networks to improve network scalability with minimized resource costs. To achieve scalability in quantum computing networks, we formulate the resource allocation problem as stochastic programming, accounting for the uncertain fidelities of qubits and entangled pairs. Furthermore, we introduce state-of-the-art reinforcement learning (RL) algorithms, from generative learning to quantum machine learning for optimal quantum resource allocation to resolve the proposed stochastic resource allocation problem efficiently. Finally, we optimize the resource allocation in heterogeneous quantum computing networks supporting quantum generative learning applications and propose a multi-agent RL-based algorithm to learn the optimal resource allocation policies without prior knowledge.

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“…量子网络堆栈与经典通信网络类似，量子网络堆栈是从量子网络底层物理实现中抽象出来的分层模型，每层通过特定的量子网络协议提供一些通信功能 [111] 。通过设计量子网络堆栈，可以进一步完善量子网络的架构，并为量子网络的建立制定标准。目前学者们提出了基于链式网络结构 [112~115] 、集群的主从式量子网络结构 [116] 和针对图态网络 [117] 的网络协议堆栈。量子经典度量 [118] 。 2. 量子网络协议量子网络协议用于实现网络运行各个阶段的功能，是保证网络正常运行和数据传输安全、可靠的基础。目前对量子网络协议的研究集中于网络路由协议，包括纠缠路由协议与密钥路由协议。纠缠路由协议在网络上选择一条建立远程纠缠的最优路径，常用度量标准有纠缠生成时间 [119] 、纠缠保真度 [120] 、端到端纠缠率 [121,122] 、纠缠生成率 [123~125] 、网络吞吐量 [126~128] 等。密钥路由协议通过选择合适的路径来实现 QKD 网络量子节点的负载均衡，对其研究多通过改进经典路由协议以适应 QKD 网络。例如， DARPA QKD 网络使用开放最短路径优先(OSPF) 协议作为密钥路由协议 [7,129] ，欧洲 SECOQC 网络使用升级版的 OSPF-v2 协议 [130] 等。也有学者针对 QKD 网络特性，以传输跳数 [131] 、剩余密钥量 [132] 等为路由度量标准来设计密钥路由协议。除网络路由协议之外，还有图态网络配置协议 [133] 、量子数据平面协议 [134] 等。这些协议与特定量子网络堆栈相关，实现网络堆栈定义的具体功能。如图态网络配置协议位于 Pirker 等人提出的量子网络堆栈的链路层，用于在网络运行时分发量子态和生成目标图态。与经典网络相比，量子网络中的路由协议更为复杂。如何综合考虑各种因素，构造合适的路由度量标准是设计量子网络路由协议的难点之一 [135] 。针对纠缠路由协议，其路由度量不仅必须根据路径长度、成本和吞吐量计算路径，而且还必须考虑所需的端到端保真度。此外，更高保真度的纠缠链路需要更多的时间来产生，这在确定路由度量标准时也必须考虑到。对于密钥路由协议，还需考虑剩余密钥数量、密钥生成速率、路由安全性等因素。量子网络协议的设计也需要考虑退相干的影响，满足量子网络的高同步与低时延要求。此外，目前量子网络的研究基于单一硬件平台的同构网络 [134] 。然而，未来的量子网络将不可避免地包括各种各样的物理平台，导致量子节点和链路的退相干和量子态保真度等参数存在差异，需要做更多的工作来了解混合量子网络中量子网络协议的性能。 (四)量子网络系统物理硬件技术 1. 量子存储器量子存储器是一种能够按照需要进行存储和读出量子态的物理设备，在量子网络中扮演着非常重要的角色。量子存储器的研究目标是要达到长存储时间、高保真度、高存取效率、大存储带宽、多模容量以及可以按需读出的实用化标准 [136] 。目前，量子存储器已经在多个体系中实现，包括原子体系 (冷原子 [137] 与室温原子 [138] ) 、固态体系(金刚石 NV 色心 [139] 和稀土掺杂晶体 [61,140,141] ) 、单量子系统(单原子 [142] 和单离子 [143] )等。所采用的量子存储协议包括电磁诱导透明协议 [144] 、原子频率梳协议 [145] 、光子回波协议 [146] 等。近年来，量子存储器在各项性能指标上均有所突破，例如，基于冷原子的存储器的存储效率最高可达到 90.6% [137] ；基于稀土掺杂晶体的量子存储器的存储时间已超 1 h [140] ，存储模式最高可达 1650…”

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Research Progress and Key Technologies of Quantum Network Systems

Li,

Gao,

Qin

et al. 2023

Strategic Study of CAE

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The rapid development of quantum information has brought new opportunities and challenges to modern information technologies. As one of the popular research directions in the field of quantum information, quantum networks aim to utilize the fundamental properties of quantum mechanics to achieve long-distance (secure) communications or provide computational capabilities superior to classical computing networks through distributed computing. The study of quantum networks holds great significance in advancing the practicality of quantum information. To gain a comprehensive understanding of the development trajectory of quantum networks, this study categorizes quantum networks into three types: quantum cryptography, quantum cloud computing, and quantum teleportation networks, based on different application scenarios and technical approaches. It provides comprehensive reviews of both domestic and international research progress and the challenges faced in each aspect. Furthermore, in conjunction with the practical implementation of quantum networks, the key technologies that need to be overcome in the development of quantum network systems, involving link establishment, information transmission, networking protocols, and physical hardware, are summarized. Overall, the development of quantum networks is still in the primary stage. At this stage, actively addressing challenges and seizing opportunities are of great significance to enhance the technological prowess of China. Therefore, to promote the development of

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Fidelity-Guaranteed Entanglement Routing in Quantum Networks

Cited by 40 publications

References 40 publications

Shortest Path Finding in Quantum Networks With Quasi-Linear Complexity

Shortest Path Finding in Quantum Networks With Quasi-Linear Complexity

Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

Research Progress and Key Technologies of Quantum Network Systems

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