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IEEE International Conference on Advanced Networks and Telecommunications Systems

Short-cuts on quantum network simulators

Anubhav Srivastava, Devendra Mishra, Madhuri Annavazzala, A. Antony Franklin, Nixon Patel, M. V. Panduranga Rao

Published Dec 13, 2021• 0 citations
Publisher

Abstract

An important idea in quantum networks is that of employing virtual edges or “short-cuts” between quantum nodes. These edges, which are shared entangled pairs between two nodes that are not directly connected “physically”, are expected to reduce the average latency of entanglement distribution in quantum network routing. In this work, we show how to create such edges on an existing discrete event simulator for quantum networks called SeQUeNCe, and study the impact that these edges have on latency. Additionally, we implement a distributed routing algorithm on the simulator and demonstrate its use in conjunction with the virtual edges. We observe a reduction in latency when short-cuts are used, as is expected. Thus, with these modifications, we believe that SeQUeNCe (and other similar simulators) can be used for experimenting with advanced quantum networking protocols.

DOI
10.1109/ants52808.2021.9936913

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An important idea in quantum networks is that of employing virtual edges or “short-cuts” between quantum nodes. These edges, which are shared entangled pairs between two nodes that are not directly connected “physically”, are expected to reduce the average latency of entanglement distribution in quantum network routing. In this work, we show how to create such edges on an existing discrete event simulator for quantum networks called SeQUeNCe, and study the impact that these edges have on latency. Additionally, we implement a distributed routing algorithm on the simulator and demonstrate its use in conjunction with the virtual edges. We observe a reduction in latency when short-cuts are used, as is expected. Thus, with these modifications, we believe that SeQUeNCe (and other similar simulators) can be used for experimenting with advanced quantum networking protocols.
Quantum routing protocols seek to distribute entanglement across different nodes of a quantum network. A recently popular approach for quantum routing is to cut down the latency times for sharing entanglement by using virtual edges in addition to physical ones. While a physical edge is associated with the presence of a quantum channel, virtual edges correspond to pre-existing entanglement between some nodes which can be leveraged for entanglement swapping. Distributed routing protocols for quantum networks have been proposed and analyzed using this idea. These analyses have also been backed up by simulations. However, to the best of our knowledge, existing simulation approaches consider a static picture, where the demands for entangled pairs are presented upfront. In this paper, we study routing algorithms through time-driven simulations. Such an approach allows for the demands to emerge in real-time as the simulation proceeds, and therefore mimic realistic scenarios better. This also facilitates studying routing protocols in the presence of dynamic replenishment of entangled pairs, and exposes issues like occurrence of deadlocks in the context of limited quantum resources. As a demonstration of the approach, we show simulation results that analyze the performance of various physical and virtual graph topologies in terms of average latency time. Finally, we show the change in performance and network saturation in the presence of replenishment of entanglement resources.
Recent advances in quantum information science enabled the development of quantum communication network prototypes and created an opportunity to study full-stack quantum network architectures. This work develops SeQUeNCe, a comprehensive, customizable quantum network simulator. Our simulator consists of five modules: hardware models, entanglement management protocols, resource management, network management, and application. This framework is suitable for simulation of quantum network prototypes that capture the breadth of current and future hardware technologies and protocols. We implement a comprehensive suite of network protocols and demonstrate the use of SeQUeNCe by simulating a photonic quantum network with nine routers equipped with quantum memories. The simulation capabilities are illustrated in three use cases. We show the dependence of quantum network throughput on several key hardware parameters and study the impact of classical control message latency. We also investigate quantum memory usage efficiency in routers and demonstrate that redistributing memory according to anticipated load increases network capacity by 69.1% and throughput by 6.8%. We design SeQUeNCe to enable comparisons of alternative quantum network technologies, experiment planning, and validation and to aid with new protocol design. We are releasing SeQUeNCe as an open source tool and aim to generate community interest in extending it.
Quantum Local Area Networks (QLANs) represent a promising building block for larger scale quantum networks with the ambitious goal -in a long time horizon- of realizing a Quantum Internet. Surprisingly, the physical topology of a QLAN can be enriched by a set of artificial links, enabled by shared multipartite entangled states among the nodes of the network. This novel concept of artificial topology revolutionizes the possibilities of connectivity within the local network, enabling an on-demand manipulation of the artificial network topology. In this paper, we discuss the implementation of the QLAN model in SeQUeNCe, a discrete-event simulator of quantum networks. Specifically, we provide an analysis of how network nodes interact, with an emphasis on the interplay between quantum operations and classical signaling within the network. Remarkably, through the modeling of a measurement protocol and a correction protocol, our QLAN model implementation enables the simulation of the manipulation process of a shared entangled quantum state, and the subsequent engineering of the entanglement-based connectivity. Our simulations demonstrate how to obtain different virtual topologies with different manipulations of the shared resources and with all the possible measurement outcomes, with an arbitrary number of nodes within the network.
A quantum network promises to enable long distance quantum communication, and assemble small quantum devices into a large quantum computing cluster. Each network node can thereby be seen as a small few qubit quantum computer. Qubits can be sent over direct physical links connecting nearby quantum nodes, or by means of teleportation over pre-established entanglement amongst distant network nodes. Such pre-shared entanglement effectively forms a shortcut - a virtual quantum link - which can be used exactly once. Here, we present an abstraction of a quantum network that allows ideas from computer science to be applied to the problem of routing qubits, and manage entanglement in the network. Specifically, we consider a scenario in which each quantum network node can create EPR pairs with its immediate neighbours over a physical connection, and perform entanglement swapping operations in order to create long distance virtual quantum links. We proceed to discuss the features unique to quantum networks, which call for the development of new routing techniques. As an example, we present two simple hierarchical routing schemes for a quantum network of N nodes for a ring and sphere topology. For these topologies we present efficient routing algorithms requiring O(log N) qubits to be stored at each network node, O(polylog N) time and space to perform routing decisions, and O(log N) timesteps to replenish the virtual quantum links in a model of entanglement generation.
A network of devices capable of transmitting quantum information called a quantum network has promising applications with vast benefits. One of the most near term achievable application is the quantum key distribution. It could be used for sharing a secret key between two end-users through any insecure authenticated communication channel. Other than sharing a secret key, a quantum network can be used for connecting quantum computers. Quantum computers have the potential to solve computational problems that their classical counterparts would require significantly more time to do so. By connecting such devices, distributed computation problems such as leader election or distributed consensus between nodes can be solved securely. For such applications to be put into practice on a large scale, there are open practical questions still to be answered. In a quantum network, a data qubit containing quantum information is transmitted by an operation called quantum teleportation. For it, two nodes need to share entanglement. Quantum teleportation then ensures the safe transmission of a qubit by using the shared entanglement and the exchange of two classical bits. This operation, however, consumes entanglement between the nodes, changing the network topology with each served request. In quantum networks, certain nodes share entanglement between each other. Routing in quantum networks entails determining which of these shared entanglements are used to transmit quantum information. As this proves to be a difficult task, we study quantum networks and in particular consider the problem of routing entanglement in quantum networks. The average latency for routing entanglement in a quantum network has been studied so far using a distributed routing approach. Thus, we present numerical simulation results of centralised routing for the average latency of demands in two existing entanglement generation models. In the first, shared entanglement between nodes is created on-demand. In the second, certain nodes pre-share entanglement before the demand comes. Our results show the intuition that using a centralised routing approach in the on-demand model results in drastically more average latency than in the model with pre-shared entanglement. Since some nodes might not be informed about the change in topology, we study the effect of the propagation of information about the network topology to nodes in the network. Our observations based on simulation results show that the average latency is significantly higher if the information about the topology is not propagated well in the network. As propagating information to all nodes in a network would be a significant load for the network, we consider information propagation within a radius and still observe a considerable decrease in average latency. At last, we present a technique called link prediction which can be performed by any node without the need for information propagation and still achieve a considerable decrease in average latency. It can be effectively used to predict the change of topology in a quantum network by using knowledge about the network topology for a certain future point in time and previous knowledge about the network traffic.
Quantum network simulators offer the opportunity to cost-efficiently investigate potential avenues for building networks that scale with the number of users, communication distance, and application demands by simulating alternative hardware designs and control protocols. Several quantum network simulators have been recently developed with these goals in mind. As the size of the simulated networks increases, however, sequential execution becomes time-consuming. Parallel execution presents a suitable method for scalable simulations of large-scale quantum networks, but the unique attributes of quantum information create unexpected challenges. In this work, we identify requirements for parallel simulation of quantum networks and develop the first parallel discrete-event quantum network simulator by modifying the existing serial simulator SeQUeNCe. Our contributions include the design and development of a quantum state manager (QSM) that maintains shared quantum information distributed across multiple processes. We also optimize our parallel code by minimizing the overhead of the QSM and decreasing the amount of synchronization needed among processes. Using these techniques, we observe a speedup of 2 to 25 times when simulating a 1,024-node linear network topology using 2 to 128 processes. We also observe an efficiency greater than 0.5 for up to 32 processes in a linear network topology of the same size and with the same workload. We repeat this evaluation with a randomized workload on a caveman network. We also introduce several methods for partitioning networks by mapping them to different parallel simulation processes. We have released the parallel SeQUeNCe simulator as an open source tool alongside the existing sequential version.