SeQUeNCe is a Python-based, discrete-event modeling and simulation package to define and study classical and quantum networks. It defines a modular framework for creating and analyzing networks and provides several hardware and protocol models. This paper demonstrates the creation and simulation of a classical network with a customized protocol and a Quantum Key Distribution (QKD) system that uses the BB84 protocol.
SeQUeNCe is a Python-based, discrete-event modeling and simulation package to define and study classical and quantum networks. It defines a modular framework for creating and analyzing networks and provides several hardware and protocol models. This paper demonstrates the creation and simulation of a classical network with a customized protocol and a Quantum Key Distribution (QKD) system that uses the BB84 protocol.
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 networks are expected to be heterogeneous systems, combining distinct qubit platforms, photon wavelengths, and device timescales to achieve scalable, multiuser connectivity. Building and iterating on such systems is costly and slow, which motivates hardware-faithful simulations that explore architecture design space and justify implementation decisions. This paper presents a framework for simulating heterogeneous quantum networks based on SeQUeNCe, a discrete-event simulator of quantum networks. We introduce faithful device models for two representative platforms - Ytterbium atoms and superconducting qubits - to implement entanglement generation and swapping protocols for time-bin encoded photons. Using extensive simulations that account for disparate clock rates and quantum frequency conversion and transduction losses/noise, we map the rate-fidelity trade space and identify the dominant bottlenecks unique to heterogeneous systems. The models are open source and extensible, enabling reproducible evaluation of future heterogeneous designs and protocols.
Quantum key distribution (QKD) can provide secure key material between two parties without relying on assumptions about the computational power of an eavesdropper. QKD is performed over quantum links and quantum networks, systems which are resource-intensive to deploy and maintain. To evaluate and optimize performance prior to, during, and after deployment, accurate simulations with attention to physical realism are necessary. Quantum network simulators can simulate a variety of quantum and classical protocols and can assist in quantum network design and optimization by offering realism and flexibility beyond mathematical models which rely on simplifying assumptions and can be intractable to solve as network complexity increases. We use a versatile discrete event quantum network simulator to simulate the entanglement-based QKD protocol BBM92 and compare it to our experimental implementation and to existing theory. We find the discrete event quantum network simulator can match experimental key rates and error rates with a lower mean squared error than analytical theory. Furthermore, we simulate secure key rates in a repeater key distribution scenario for which no experimental implementations exist and find agreement between simulation and analytical theory. Hence, we demonstrate discrete event simulators can meet needs in quantum network simulations which cannot be filled solely by experiment or theory: discrete event simulators can accurately simulate QKD protocols and match experiments in regimes where theoretical models may require more simplifying assumptions, and they can match theoretical models in the opposite scenario where experiments have not yet been performed but theoretical models exist.
Quantum networks are expected to be heterogeneous systems, combining distinct qubit platforms, photon wavelengths, and device timescales to achieve scalable, multiuser connectivity. Building and iterating on such systems is costly and slow, which motivates hardware-faithful simulations that explore architecture design space and justify implementation decisions. This paper presents a framework for simulating heterogeneous quantum networks based on SeQUeNCe, a discrete-event simulator of quantum networks. We introduce faithful device models for two representative platforms–Ytterbium atoms and superconducting qubits– to implement entanglement generation and swapping protocols for time-bin encoded photons. Using extensive simulations that account for disparate clock rates and quantum frequency conversion and transduction losses/noise, we map the rate–fidelity trade space and identify the dominant bottlenecks unique to heterogeneous systems. The models are open source and extensible, enabling reproducible evaluation of future heterogeneous designs and protocols.
With recent advances in the fields of quantum information theory [J. Pablo. Nature 12, 2172 (2021)] and the approach of the Noisy Intermediate-Scale Quantum (NISQ) [J. Preskill. Quantum 2, 79 (2018)] computing era, it is necessary to provide tools for experimentation and prototyping that are able to keep pace with the rapidly progressing field of quantum computing. SeQUeNCe, an open source simulator of quantum network communication, aims to provide scalability and extensibility for the simulation of quantum networks, from the hardware level to the application and protocol level. In order to improve upon the usability of this software, we implement a graphical user interface which maintains the core principles of SeQUeNCe, scalability and extensibility, while enhancing the software's portability and ease of use. We demonstrate the capabilities of the graphical user interface through the construction of the existing Chicago metropolitan quantum network topology.
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.