[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-86483-en":3,"doc-seo-86483-105":30,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},86483,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Model-Driven Digital Twin Framework for Quantum Networks","Quantum networks are moving toward larger, more operational infrastructures, but evaluation is still fragmented across distinct physical platforms, simulators, protocols, and architectural abstractions. Existing digital-twin work often delivers isolated functions or application-specific solutions instead of reusable, system-level twins. The paper argues that Model-Driven Engineering (MDE) enables systematic integration and evolution of heterogeneous artefacts, defining requirements for design-time evaluation and runtime synchronisation and outlining architecture progression toward interoperable digital twins.","Model-Driven Digital Twin Framework for Quantum Networks  \nAmal Elsokary [A.Elsokary@lboro.ac.uk](A.Elsokary@lboro.ac.uk)[ ](A.Elsokary@lboro.ac.uk)Loughborough University  \nLoughborough, UK  \nHayato Ishida  \n[H.Ishida@lboro.ac.uk](H.Ishida@lboro.ac.uk)[ ](H.Ishida@lboro.ac.uk)Loughborough University  \nLoughborough, UK  \nRan Wei[r.wei5@lancaster.ac.uk](r.wei5@lancaster.ac.uk)[ ](r.wei5@lancaster.ac.uk)Lancaster University  \nLancaster University, UK  \nMichael J. de C. Henshaw  \n[M.J.d.Henshaw@lboro.ac.uk](M.J.d.Henshaw@lboro.ac.uk)[ ](M.J.d.Henshaw@lboro.ac.uk)Loughborough University  \nLoughborough, UK  \nSiyuan Ji  \n[S.Ji@lboro.ac.uk](S.Ji@lboro.ac.uk)[ ](S.Ji@lboro.ac.uk)Loughborough University  \nLoughborough, UK  \narXiv :2607 . 10367v 1 [ cs . SE] 11 Jul 2026  \nAbstract  \nQuantum 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.  \nCCS Concepts  \n• Software and its engineering → Model-driven software engineering; Software architectures; • Computer systems organization → Embedded and cyber-physical systems.  \nKeywords  \nDigital twin, model-driven engineering, quantum networks, quantum network simulation, SysML v2  \n1 Introduction  \nQuantum networks (QNs) are progressing from experimental demonstrations towards increasingly deployed and scalable infrastructures, enabling applications in secure communication, distributed quantum sensing, and distributed quantum computing [16] . This progression is accompanied by continuing advances in quantum photonic devices, communication and entanglement-distribution protocols, network architectures, and control mechanisms. However, relying solely on physical experimentation and deployment to evaluate new technologies and network configurations can be costly and time-consuming and is often constrained by equipment availability, configuration complexity, and experimental risks [31] .  \nMoreover, the heterogeneous and interconnected nature of QNs makes it difficult to understand their overall behaviour, predict their performance under emerging conditions, and evaluate the integration of new technologies into existing network environments  \n[29] . Their practical adoption therefore requires not only an understanding of individual physical technologies, but also a system-level representation of the interactions and dependencies among components, services, protocols, control functions, and architectural layers [22] .  \nThese challenges create a need for a structured framework capable of supporting anomaly detection, resource optimisation, technology integration, and the assessment of alternative deployment decisions [28]. A digital twin (DT) perspective can address this need by virtually representing network components, services, interfaces, and physical characteristics to explore configurations, analyse behaviour, predict performance, and assess technologies before and during physical deployment [45] .  \nResearch on DT for QNs is emerging, with recent studies addressing remote access to experimental data, attack and imperfection analysis, performance optimisation, and monitoring and control of terrestri","cbCaieQeNDnMfMYs","https://ap.wps.com/l/cbCaieQeNDnMfMYs","pdf",1730076,4,1,10,"English","en",105,"# Abstract\n# Introduction\n## Challenges in evaluating quantum networks\n## Digital twin research status and limitations\n## Need for an MDE-based engineering foundation","[{\"question\":\"How does the proposed framework use MDE to address the identified challenges?\",\"answer\":\"The framework treats models as explicit, processable artefacts and uses metamodels, transformations, model management, and automation to connect system-level representations with domain-specific simulations, monitoring services, and physical interfaces. It targets consistent, traceable models across physical and digital environments for design-time evaluation and runtime synchronization.\"}]",1784212062,25,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":28},"model-driven-digital-twin-framework-for-quantum-networks","",{"@graph":36,"@context":77},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":20},"https://docshare.wps.com/document/model-driven-digital-twin-framework-for-quantum-networks/86483/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-28","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71],{"name":72,"@type":73,"acceptedAnswer":74},"How does the proposed framework use MDE to address the identified challenges?","Question",{"text":75,"@type":76},"The framework treats models as explicit, processable artefacts and uses metamodels, transformations, model management, and automation to connect system-level representations with domain-specific simulations, monitoring services, and physical interfaces. 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