Model-Driven Digital Twin Framework for Quantum Networks

2026-07-11

AI Summary

This work addresses the fragmentation in current quantum network evaluation across heterogeneous platforms, simulators, and protocols, which lacks a reusable, system-level digital twin solution. To bridge this gap, the study systematically introduces Model-Driven Engineering (MDE) to construct a digital twin framework for quantum networks that supports both design-time assessment and runtime synchronization. It proposes an architectural evolution path transitioning from code-driven integration toward a hub-and-spoke paradigm. A proof-of-concept implementation leverages SysML v2 modeling, a QKD kit, an EMF-based controller, and the SeQUeNCe simulation platform, demonstrating unified modeling of heterogeneous components, evolvable integration, and multi-layer interoperability. This approach establishes an adaptable and verifiable foundational infrastructure for quantum networks.

Abstract

Quantum networks are advancing towards larger and more operational infrastructures, yet their evaluation remains fragmented across heterogeneous physical platforms, simulators, protocols, and architectural abstractions. Current digital-twin studies for quantum networks mainly realise isolated capabilities or application-specific solutions rather than reusable system-level twins. This paper argues that Model-Driven Engineering (MDE) can provide a systematic basis for integrating and evolving these heterogeneous artefacts. It derives requirements for design-time evaluation and runtime synchronisation, and proposes a progression of architectures from code-driven and domain-model-driven solutions to point-to-point and hub-and-spoke integration. A conceptual implementation case study illustrates this using SysML v2, QKD kit, an EMF-based controller, and SeQUeNCe. The work provides a foundation for adaptable and interoperable digital twins for quantum networks.

Problem

• Quantum Networks
• Digital Twin
• Model-Driven Engineering
• Heterogeneous Integration
• System-Level Evaluation

Innovation

• Model-Driven Engineering
• Digital Twin
• Quantum Networks
• SysML v2
• Interoperability