Cross-Validating Quantum Network Simulators

TL;DR

This work tackles the reliability and reproducibility of quantum-network simulations by cross-validating two open-source simulators, QuISP and SeQUeNCe, on fundamental primitives like base Bell-pair generation and entanglement swapping. The authors implement three benchmark experiments targeting the time to distribute $N_{ ext{Bell}}=1000$ Bell pairs and the fidelity of the end-to-end entanglement, comparing results against analytical models. They find a constant-factor difference in timing due to distinct connection-handshake approaches, while end-to-end fidelities converge under identical error parameters, indicating consistency in error modeling. The study provides a practical benchmarking methodology and a path toward more reliable simulator-based protocol development for future quantum networks.

Abstract

We present a first cross-validation of two open-source quantum network simulators, QuISP and SeQUeNCe, focusing on basic networking tasks to ensure consistency and accuracy in simulation outputs. Despite very similar design objectives of both simulators, their differing underlying assumptions can lead to variations in simulation results. We highlight the discrepancies in how the two simulators handle connections, internal network node processing time, and classical communication, resulting in significant differences in the time required to perform basic network tasks such as elementary link generation and entanglement swapping. We devise common ground scenarios to compare both the time to complete resource distribution and the fidelity of the distributed resources. Our findings indicate that while the simulators differ in the time required to complete network tasks, a constant factor difference attributable to their respective connection models, they agree on the fidelity of the distributed resources under identical error parameters. This work demonstrates a crucial first step towards enhancing the reliability and reproducibility of quantum network simulations, as well as leading to full protocol development. Furthermore, our benchmarking methodology establishes a foundational set of tasks for the cross-validation of simulators to study future quantum networks.

Figures (7)

• Figure 1: (a) Entanglement generation using photonic Bell-state measurement (BSM) at the Bell-state analyzer (BSA) in the memory-interference-memory (MIM) link architecture. Success probability is denoted by $p_{\text{BSM}}$. (b) After successful generation of two neighboring links, the repeater performs entanglement swapping on its quantum memories to create an end-to-end entangled connection.
• Figure 2: (a) Quantum Router Software Architecture (QRSA) used in QuISP to control the behavior of network nodes. (b) SeQUeNCe software framework comprises a simulation kernel and five other modules.
• Figure 3: (a) Sequence diagram for link-level entanglement generation in QuISP. The photon train is represented by a single arrow. (b) Timing analysis for the entanglement generation protocol in SeQUeNCe. Classical messages are represented by black arrows and quantum messages by green arrows.
• Figure 4: (a) Verification of end-to-end fidelity Eq. (\ref{['eq:quisp-swap-fidelity-perfect-memory']}) for QuISP. Blue diamonds for varying $p_{\text{g}}$ and $p_{\text{m}}=0.1$ and yellow hexagons for varying $p_{\text{m}}$ with $p_{\text{g}}=0.05$. Dashed lines represent our theoretical predictions. (b) Verification of Eq. (\ref{['eq:quisp-swap-fidelity-with-decoherence']}) for $p_{\text{g}}=0.05$ and $p_{\text{m}}=0.1$, varying degree of depolarizing noise.
• Figure 5: Verification of SeQUeNCe error models. (a) Without decoherence. Blue diamonds for $p_{\text{m}}=0.1$ and yellow hexagons for $p_{\text{g}}=0.05$. (b) Including decoherence for $p_{\text{g}}=0.05$ and $p_{\text{m}}=0.1$.