Simulations of Photonic Quantum Networks for Performance Analysis and Experiment Design

Wu, Xiaoliang; Chung, Joaquín; Kolar, Alexander; Wang, Eugene; Zhong, Tian; Kettimuthu, Rajkumar; Suchara, Martin

doi:10.1109/photonics49561.2019.00010

Cited by 12 publications

(15 citation statements)

References 31 publications

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“…We first use the sequential QKD simulator developed in our prior work [39,40] to study the behavior of QKD networks. The metrics include the type of simulation events, the execution speed of different event types, and the distribution of each type of event.…”

Section: Analysis Of Sequential Simulation Of Qkd Networkmentioning

confidence: 99%

See 1 more Smart Citation

A Scalable Quantum Key Distribution Network Testbed Using Parallel Discrete-Event Simulation

Zhang

Chen

et al. 2022

ACM Trans. Model. Comput. Simul.

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Quantum key distribution (QKD) has been promoted as a means for secure communications. Although QKD has been widely implemented in many urban fiber networks, the large-scale deployment of QKD remains challenging. Today, researchers extensively conduct simulation-based evaluations for their designs and applications of large-scale QKD networks for cost efficiency. However, the existing discrete-event simulators offer models for QKD hardware and protocols based on sequential event execution, which limits the scale of the experiments. In this work, we explore parallel simulation of QKD networks to address this issue. Our contributions lay in the exploration of QKD network characteristics to be leveraged for parallel simulation as well as the development of a parallel simulation framework for QKD networks. We also investigate three techniques to improve the simulation performance including (1) a ladder queue based event list, (2) memoization for computationally intensive quantum state transformation information, and (3) optimization of the network partition scheme for workload balance. The experimental results show that our parallel simulator is 10 times faster than a sequential simulator when simulating a 128-node QKD network. Our linear-regression-based network partition scheme can further accelerate the simulation experiments up to two times over using a randomized network partition scheme.

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Section: Analysis Of Sequential Simulation Of Qkd Networkmentioning

confidence: 99%

“…However, the sequential simulation approach significantly limits the scale of simulated quantum networks. For example, using sequential simulation [39,40] takes around 184 seconds to simulate 20 ms of a 128-node QKD network (see Figure 10(a) in Section 7 for detailed experimental settings).…”

Section: Introductionmentioning

confidence: 99%

A Scalable Quantum Key Distribution Network Testbed Using Parallel Discrete-Event Simulation

Zhang

Chen

et al. 2022

ACM Trans. Model. Comput. Simul.

Self Cite

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“…This work also significantly redesigned the Simulation Kernel to allow parallel simulations. Further details about the design and use cases of the sequential version of the SeQUeNCe simulator can be found in our earlier work [47][48][49].…”

Section: Sequence: a Customizable Quantum Network Simulatormentioning

confidence: 99%

Parallel Simulation of Quantum Networks with Distributed Quantum State Management

Wu¹,

Kolar²,

Chung³

et al. 2021

Preprint

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Quantum network simulators offer the opportunity to cost-efficiently investigate potential avenues to 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. However, as the size of the simulated networks increases, 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 some 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 SeQUeNCe simulator. 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 among processes. Using these techniques, we observe a speedup of 2 to 25 times when simulating a 1,024-node linear network with 2 to 128 processes. We also observe 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. Finally, we also introduce several methods for partitioning networks by mapping them to different parallel simulation processes. We released the parallel SeQUeNCe simulator as an open-source tool alongside the existing sequential version.

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“…The variety of materials platforms [41] for the quantum network components make the design of quantum networks a challenging engineering task. Preliminary simulations are necessary for designing optical-fiber classical connections specifically for quantum networks [42][43][44][45][46][47]. This kind of simulation allows a designer to construct the most tolerant protocol to account for classical network ping, single-photon traveling time fluctuations, and other parameter imperfections in the quantum network hardware and evaluate if the existing hardware satisfies the error-robustness requirements.…”

Section: Introductionmentioning

confidence: 99%

“…Here we analyze the entanglement generation capabilities between the end-nodes in a simple linear network using SeQEeNCe quantum network simulator [43,45]. We examine the two protocols discussed above in detail, applied towards the generation of elementary links between adjacent nodes.…”

Section: Introductionmentioning

confidence: 99%

Entanglement generation in a quantum network with finite quantum memory lifetime

Semenenko,

Hu,

Figueroa

et al. 2021

Preprint

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We simulate entanglement sharing between two end-nodes of a quantum network using Se-QUeNCe, an open-source simulation package for quantum networks. Our focus is on the rate of entanglement generation between the end-nodes with many repeaters with a finite quantum memory lifetime. Our findings demonstrate that the performance of quantum connection depends highly on the entanglement management protocol scheduling entanglement generation and swapping, resulting in the final end-to-end entanglement. Numerical and analytical simulations show limits of connection performance for a given number of repeaters involved, memory lifetimes for a given distance between the end nodes, and an entanglement management protocol.

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Simulations of Photonic Quantum Networks for Performance Analysis and Experiment Design

Cited by 12 publications

References 31 publications

A Scalable Quantum Key Distribution Network Testbed Using Parallel Discrete-Event Simulation

A Scalable Quantum Key Distribution Network Testbed Using Parallel Discrete-Event Simulation

Parallel Simulation of Quantum Networks with Distributed Quantum State Management

Entanglement generation in a quantum network with finite quantum memory lifetime

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