SeQUeNCe: A Customizable Discrete-Event Simulator of Quantum Networks

Wu, Xiaoliang; Kolar, Alexander; Chung, Joaquín; Jin, Dong; Zhong, Tian; Kettimuthu, Rajkumar; Suchara, Martin

doi:10.48550/arxiv.2009.12000

Cited by 9 publications

(10 citation statements)

References 58 publications

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“…Apart from QKD simulators, people also develop simulators for quantum internet [23]. Se-QUeNCe [41], Netsquid [14], and QuISP [26] are three sequential discrete-event simulators for quantum networks that aim to transmit quantum information. SQUANCH [4] is a simulator for quantum internet that supports parallel simulation.…”

Section: Related Workmentioning

confidence: 99%

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: Related Workmentioning

confidence: 99%

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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“…The results of this section have already been applied to analyze quantum repeaters [viii][xi] [xii] and have been included in software for simulating quantum networks [222].…”

Section: Spin-spin Entanglementmentioning

confidence: 99%

Modelling Markovian light-matter interactions for quantum optical devices in the solid state

Wein

2021

Preprint

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The desire to understand the interaction between light and matter has stimulated centuries of research, leading to technological achievements that have shaped our world. One contemporary frontier of research into light-matter interaction considers regimes where quantum effects dominate.By understanding and manipulating these quantum effects, a vast array of new quantum-enhanced technologies become accessible. In this thesis, I explore and analyze fundamental components and processes for quantum optical devices with a focus on solid-state quantum systems. This includes indistinguishable single-photon sources, deterministic sources of entangled photonic states, photonheralded entanglement generation between remote quantum systems, and deterministic opticallymediated entangling gates between local quantum systems. For this analysis, I make heavy use of an analytic quantum trajectories approach applied to a general Markovian master equation of an optically-active quantum system, which I introduce as a photon-number decomposition. This approach allows for many realistic system imperfections, such as emitter pure dephasing, spin decoherence, and measurement imperfections, to be taken into account in a straightforward and comprehensive way.Throughout this thesis, I will be using the above roman numeral references whenever citing works where I am a co-author. However, not all of these papers are relevant to the present topic.The papers [iii] and [ix] are the only two that are entirely included in this thesis, and the author contributions for these works are summarized below. Please also see appendix C for copyright permissions.Author contributions for [iii]-SW and CS conceived the idea. SW and RG developed the methods. SW performed the analysis and wrote the manuscript with guidance from NL and RG.NL and CS provided critical feedback. All authors contributed to editing the manuscript.Author contributions for [ix]-SCW and CS conceived the idea. SCW developed the methods.SCW performed the analysis and wrote the manuscript with help from JWJ, YFW, and FKA. RG and CS provided critical feedback. All authors contributed to editing the manuscript.A portion of supplementary theory material from [xiii] and [xiv] are also described in this thesis under fair dealing, as I was the primary author of that material within those experimental papers. Moreover, I will include unpublished research related to my contributions to [vii] and [viii].

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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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SeQUeNCe: A Customizable Discrete-Event Simulator of Quantum Networks

Cited by 9 publications

References 58 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

Modelling Markovian light-matter interactions for quantum optical devices in the solid state

Entanglement generation in a quantum network with finite quantum memory lifetime

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