NetSquid, a NETwork Simulator for QUantum Information using Discrete events
At a Glance
Section titled âAt a Glanceâ| Metadata | Details |
|---|---|
| Publication Date | 2021-07-16 |
| Journal | Communications Physics |
| Authors | Tim Coopmans, Robert Knegjens, Axel Dahlberg, David Maier, Loek Nijsten |
| Institutions | SURFsara (Netherlands), SURF |
| Citations | 187 |
| Analysis | Full AI Review Included |
Executive Summary
Section titled âExecutive SummaryâNetSquid (NETwork Simulator for Quantum Information using Discrete events) is a modular, discrete-event simulation platform designed to model complex quantum networks and modular quantum computing systems.
- Core Value Proposition: NetSquid provides a versatile design tool capable of accurately modeling physical non-idealities (e.g., time-dependent decoherence, gate errors) and complex classical control planes within large-scale quantum networks.
- Modular Design: The framework allows flexible stacking of hardware models (e.g., Nitrogen Vacancy centers, Atomic Frequency Combs (AFC), Electronically Induced Transparency (EIT) memories) and control protocols.
- Scalability Demonstrated: The platform successfully simulated entanglement distribution over a chain of up to 1000 nodes, leveraging specialized quantum state formalisms (Stabilizer Tableaus, Graph States with Local Cliffords) to manage state space size.
- Protocol Validation: NetSquid was used to analyze a quantum switch control plane, extending performance estimates beyond its analytically known regime and incorporating memory dephasing noise.
- Hardware Benchmarking: Simulations compared the performance (secret key rate, fidelity) of repeater chains based on two distinct atomic-ensemble memory types (AFC vs. EIT) across varying distances.
- Performance Sensitivity: Analysis of NV repeater chains identified detection probability as the most critical hardware parameter for achieving high entanglement fidelity with the SWAP-ASAP protocol.
Technical Specifications
Section titled âTechnical SpecificationsâThe following data points relate to the simulation capabilities and the hardware models benchmarked within the NetSquid framework.
| Parameter | Value | Unit | Context |
|---|---|---|---|
| Maximum Simulated Nodes | 1000 | Nodes | Repeater chain scalability benchmark |
| Maximum Simulated Distance | 1500 | km | NV Repeater Chain analysis range |
| Quantum State Formalisms | 4 | Types | KET, Density Matrix (DM), Stabilizer Tableau (STAB), Graph State with Local Cliffords (GSLC) |
| Universal Formalism Scaling (KET) | 2n | - | Memory/time scaling with n qubits |
| Universal Formalism Scaling (DM) | 22n | - | Memory/time scaling with n qubits |
| Classical Fidelity Threshold | 0.5 | - | Minimum fidelity required for successful entanglement |
| NV Repeater Fidelity (3x Improvement) | 0.39 | - | SWAP-ASAP protocol, 500 km distance |
| Quantum Switch T2 Analysis Range | Up to 10 | ”s | Memory coherence time (T2) analysis |
| Atomic Ensemble Crossover Distance | ~50 | km | Distance where AFC memories begin to outperform EIT memories |
| NV Detection Probability Improvement | 2x to 50x | Factor | Parameter yielding the largest fidelity increase in sensitivity analysis |
Key Methodologies
Section titled âKey MethodologiesâThe NetSquid simulation relies on integrating several key technologies to achieve accuracy, modularity, and scalability.
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Discrete-Event Simulation (DES):
- The simulation progresses time by stepping through a sequence of discrete events (e.g., qubit arrival, measurement, classical message receipt).
- This approach efficiently handles complex control processes and asynchronous feedback loops characteristic of quantum networks.
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Modular Component Framework:
- All hardware elements (nodes, channels, quantum processors) are modeled as hierarchical components with defined classical and quantum communication ports.
- Physical models (e.g., FibreLoss Model, Decoherence Model) are assigned to these components to characterize non-ideal behavior.
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Dynamic Quantum State Tracking:
- Quantum information is tracked at the qubit level, where qubits dynamically share quantum states (merge/split) upon entanglement or measurement.
- Decoherence and time-dependent noise are accurately tracked by retroactively updating quantum states based on the elapsed time between events.
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Stochastic Sampling and Parallel Execution:
- Quantum operations requiring a singular classical outcome (e.g., measurement) are probabilistically sampled, leading to complex stochastic paths for a single run.
- Performance metrics are determined by statistically averaging results from many independent runs, which are typically executed in parallel on computing clusters.
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Quantum State Formalism Selection:
- NetSquid supports multiple formalisms: Ket vectors (KET) and Density Matrices (DM) for universal computation, and Stabilizer Tableaus (STAB) and Graph States with Local Cliffords (GSLC) for scalable, sub-exponential simulation of Clifford-based protocols.
Commercial Applications
Section titled âCommercial ApplicationsâNetSquid serves as a crucial software tool for the design and validation phases of next-generation quantum technologies.
- Quantum Internet Architecture: Used for designing, validating, and optimizing the entire quantum network stack, including link layer protocols and network control planes (e.g., quantum switches and routers).
- Quantum Hardware Development: Provides a platform to predict the required performance thresholds (fidelity, coherence time, detection efficiency) for near-term quantum hardware (e.g., NV centers, atomic ensembles) necessary to achieve target network rates.
- Modular Quantum Computing: Applicable to studying the scalability and timing constraints of distributed quantum computing architectures where control plane timing is critical for overall performance.
- Protocol Benchmarking: Enables rapid comparison and benchmarking of different quantum repeater protocols (e.g., SWAP-ASAP vs. NESTED-WITH-DISTILL) on identical, realistic hardware models.
- System Integration and Timing Analysis: Essential for investigating the intricate interplay between classical control messages, feedback loops, and time-dependent quantum noise (decoherence) across a network.
View Original Abstract
Abstract In order to bring quantum networks into the real world, we would like to determine the requirements of quantum network protocols including the underlying quantum hardware. Because detailed architecture proposals are generally too complex for mathematical analysis, it is natural to employ numerical simulation. Here we introduce NetSquid, the NETwork Simulator for QUantum Information using Discrete events, a discrete-event based platform for simulating all aspects of quantum networks and modular quantum computing systems, ranging from the physical layer and its control plane up to the application level. We study several use cases to showcase NetSquidâs power, including detailed physical layer simulations of repeater chains based on nitrogen vacancy centres in diamond as well as atomic ensembles. We also study the control plane of a quantum switch beyond its analytically known regime, and showcase NetSquidâs ability to investigate large networks by simulating entanglement distribution over a chain of up to one thousand nodes.