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arXiv:2212.08809 · IEEE International Conference on Quantum Computing and Engineering (QCE)

Simulation of Entanglement Generation between Absorptive Quantum Memories

Allen Zang, Alexander Kolar, Joaquín Chung, Martin Suchara, Tian Zhong, Rajkumar Kettimuthu

Published Sep 1, 2022• 10 citations
arXivHTMLPDF

Abstract

Quantum entanglement is an essential resource for quantum networks. However, the generation of entanglement between physical devices at remote network nodes is a challenging task towards practical implementation of quantum networks. In this work, we use the open-source Simulator of QUantum Network Communication (SeQUeNCe), developed by our team, to simulate entanglement generation between two atomic frequency comb (AFC) absorptive quantum memories to be deployed on the Argonne-Chicago quantum network. We realize the representation of photonic quantum states within truncated Fock spaces in SeQUeNCe and build models for a spontaneous parametric down-conversion (SPDC) source, AFC absorptive quantum memories, and measurement devices with non-number-resolving photon detectors. Based on these developments, we observe varying fidelity with SPDC source mean photon number, and varying entanglement generation rate with both mean photon number and memory mode number. We also simulate tomographic reconstruction of the effective density matrix for the bipartite photonic states retrieved from quantum memories. Our work extends the usability of the SeQUeNCe simulator with new hardware modules and Fock state representation that will improve the simulation of near term quantum network hardware and protocols.

DOI
10.1109/qce53715.2022.00084

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Quantum entanglement is an essential resource for quantum networks. However, the generation of entanglement between physical devices at remote network nodes is a challenging task towards practical implementation of quantum networks. In this work, we use the open-source Simulator of QUantum Network Communication (SeQUeNCe), developed by our team, to simulate entanglement generation between two atomic frequency comb (AFC) absorptive quantum memories to be deployed on the Argonne-Chicago quantum network. We realize the representation of photonic quantum states within truncated Fock spaces in SeQUeNCe and build models for a spontaneous parametric down-conversion (SPDC) source, AFC absorptive quantum memories, and measurement devices with non-number-resolving photon detectors. Based on these developments, we observe varying fidelity with SPDC source mean photon number, and varying entanglement generation rate with both mean photon number and memory mode number. We also simulate tomographic reconstruction of the effective density matrix for the bipartite photonic states retrieved from quantum memories. Our work extends the usability of the SeQUeNCe simulator with new hardware modules and Fock state representation that will improve the simulation of near term quantum network hardware and protocols.
Quantum entanglement is an essential resource for quantum networks, thus generation and distribution of entanglement between remote network nodes are two important tasks faced by practical implementation of quantum networks. Given that the number and scale of real quantum network testbeds are still limited we use simulation to study entanglement generation and distribution, aiming at providing insight and guidance for quantum network construction. We extend the functionality of the open-source Simulator of QUantum Network Communication (SeQUeNCe) developed by our group to support representation of quantum state under Fock basis, and use it to simulate entanglement generation between two atomic frequency comb (AFC) absorptive quantum memories. Regarding entanglement distribution, based on the so-called continuous generation scheme, we propose an adaptive scheme that uses history request information to better guide the choice of randomly generated quantum links before receiving future requests. We demonstrate the concept and power of our adaptive scheme, and explore relevant quantum memory allocation scenarios through simulation.
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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.
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.
Different quantum systems possess different favorable qualities. On the one hand, ensemble-based quantum memories are suited for fast multiplexed long-range entanglement generation. On the other hand, single-atomic systems provide access to gates for processing of information. Both of those can provide advantages for high-rate entanglement generation within quantum networks. We develop a hybrid architecture that takes advantage of these properties by combining trapped-ion nodes and nodes comprised of spontaneous parametric down conversion photon pair sources and absorptive memories based on rare-earth ion ensembles. To this end, we solve the central challenge of matching the different bandwidths of photons emitted by those systems in an initial entanglement-generation step. This enables the parallel execution of multiple probabilistic tasks in the initial stage. As a particular example, we show that our approach can lead to a significant speed-up for the fundamental task of creating ion-ion entanglement over hundreds of kilometers in a quantum network.