A quantum computer network

Cheng Li Wu

Lijun Ma, Lei Ding

Edge computing network and quantum network are two emerging technologies in current communication fields. Edge computing has emerged to support the computational demand of delay-sensitive applications in which substantial computing and storage are deployed at the network edge close to data sources. Quantum network supports distributed quantum computing, which could provide exponentially computation capabilities for certain problems. The vision of a hybrid quantum-edge is to provide a fundamentally new computing paradigm by expanding the computing capabilities and security of edge computing with quantum computing and quantum communications. The distributed nature of edge computing networks will also enable new scalable quantum networking schemes and applications. Such a hybrid computing paradigm will achieve unparalleled capabilities that are provably impossible by using only classical computing or quantum computing schemes alone. In this paper, we introduce the concept of hybrid quantum-edge computing network and discuss its challenges and opportunities.

Peckham, Jacob Edward

Quantum computing is expected to solve problems that classical computing cannot solve efficiently. The size of problems that a quantum computer can solve is directly linked to the number of fault-tolerant or error corrected qubits a quantum computer has. Distributed quantum computing allows for problems with higher qubit counts to be solved, even if each computer in the system does not have enough qubits on its own. Current work on distributed quantum computing has major gaps, with few works that propose overall architectures for distributed quantum computing. This work proposes two network designs for distributed quantum computing applications. One network is a passive optical network, the other network uses active switching. Both proposed networks use existing, or near future technologies that have been experimentally demonstrated to give reasonable approximations of what near future distributed quantum computing could look like. The goal is to highlight some of the gaps in current research and propose some initial work to solve these problems such as, network traffic patterns, coordination of classical and quantum communication, and the interface between the network and quantum nodes. Mathematical analysis and simulation are used to give some bounds on how future designers can expect a distributed quantum network to behave: the computational cost of distributed quantum operations, what types of data rates are possible, and how errors in the network effect end user quality of service. The configurations tested in this work show that the passive quantum network has usable performance, with distributed operations well below qubit decoherence times of systems like IBM Eagle r3. The active network proposed also has acceptable runtimes for distributed operations, but is unable to sustain data rates expected to be required for distributed quantum operations.

Yongshan Ding, Frederic T. Chong

Günter Mahler A, Volker A. Weberruß

Tianshun Wang, Minghui Dai, Haiyan Guo +3 more

To address the security and resource challenges in traditional marine edge computing networks (MECNs), this article proposes a quantum-empowered marine edge computing network (QMN) architecture. QMN enhances the edge computing performance in marine scenarios through a multi-layered approach, including the underwater, surface, and aerial layers. Specifically, QMN employs quantum sensors across multiple layers in the marine network to improve environmental monitoring with superior sensitivity and accuracy. Then, quantum communication ensures the security of data transmission and task offloading against interception and eavesdropping attacks, while quantum computing accelerates the processing of complex maritime tasks and improves operational efficiency. Additionally, wireless quantum charging provides a sustainable energy solution to support continuous operation in challenging marine environments. Furthermore, by integrating four proposed novel quantum technologies into QMN, this architecture achieves superior monitoring, highly secure transmission, efficient task processing and energy supply capabilities for MECNs. A case study simulates the quantum task offloading and quantum edge computing within QMN. Simulation results demonstrate the improvement of security and computational performance achieved by QMN. Open research directions for quantum restrictions in QMN are also discussed.