Research on quantum communication networks has grown rapidly in recent years, driven by progress in quantum devices, simulators, and experimental testbeds. As these systems become more complex, there is increasing interest in digital methods that can support analysis, prediction, and performance assessment without relying exclusively on physical experimentation. Surveying articles from 1984 to 2025, this systematic literature review examines the current state of digitalisation in quantum communication networks. It evaluates how existing tools and studies contribute to the longer-term goal of creating digital twin technologies for quantum systems. Using PRISMA, a structured and transparent review process, the literature is grouped into three categories that reflect different levels of digital representation: digital models, digital shadows, and initial attempts that resemble early digital twin practices. The findings show that the community has developed sophisticated simulation platforms and a wide range of modelling approaches, and that several experimental testbeds already support partial data-driven integration. However, the review also shows that continuous synchronisation between physical quantum networks and their digital counterparts remains largely undeveloped. The study identifies the main technical gaps that prevent deeper cyber-physical integration and outlines research directions that could guide the development of future digital frameworks capable of supporting prediction, optimisation, and system-level evaluation across the full lifecycle of quantum communication networks.
Research on quantum communication networks has grown rapidly in recent years, driven by progress in quantum devices, simulators, and experimental testbeds. As these systems become more complex, there is increasing interest in digital methods that can support analysis, prediction, and performance assessment without relying exclusively on physical experimentation. Surveying articles from 1984 to 2025, this systematic literature review examines the current state of digitalisation in quantum communication networks. It evaluates how existing tools and studies contribute to the longer-term goal of creating digital twin technologies for quantum systems. Using PRISMA, a structured and transparent review process, the literature is grouped into three categories that reflect different levels of digital representation: digital models, digital shadows, and initial attempts that resemble early digital twin practices. The findings show that the community has developed sophisticated simulation platforms and a wide range of modelling approaches, and that several experimental testbeds already support partial data-driven integration. However, the review also shows that continuous synchronisation between physical quantum networks and their digital counterparts remains largely undeveloped. The study identifies the main technical gaps that prevent deeper cyber-physical integration and outlines research directions that could guide the development of future digital frameworks capable of supporting prediction, optimisation, and system-level evaluation across the full lifecycle of quantum communication networks.
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.
Quantum technologies have emerged as critical enablers of next-generation communication, computation, and sensing systems. This review aims to assess the current state of Quantum Key Distribution (QKD) and related quantum technologies by examining recent empirical findings, methodological innovations, and systemic challenges. A structured literature search was conducted across Scopus, PubMed, and Google Scholar using Boolean keyword combinations targeting QKD, quantum sensing, and communication applications. The review focused on peer-reviewed articles from the last five years and included experimental studies, simulations, and applied case analyses. Findings show that QKD has demonstrated remarkable reliability in both controlled laboratory and real-world settings. Studies on multicore fiber networks highlight the potential for high-dimensional communication security, while comparative analyses reveal disparities between implementation strategies across different regions. However, systemic challenges such as inadequate infrastructure, inconsistent regulation, and insufficient public understanding hinder wide-scale adoption. The discussion identifies critical factors contributing to these challenges and proposes actionable policy recommendations, including increased investment in infrastructure, standardized regulations, and targeted education programs. This review concludes that achieving the full potential of quantum technologies will require integrative strategies addressing technical, institutional, and social dimensions. Future research should emphasize longitudinal evaluation and interdisciplinary collaboration to enhance scalability and impact. The insights offered here provide a foundational framework for policymakers, researchers, and industry leaders to advance the adoption of secure, scalable quantum systems.
The integration of Artificial Intelligence (AI) into the field of quantum communication has emerged in recent years as a promising avenue for enhancing secure data transmission, error correction, and scalability in quantum networks. This paper offers a comprehensive survey of AI applications in quantum communication, with a focus on machine learning (ML) models such as neural networks and reinforcement learning, which are adapted to manage complex quantum challenges. Despite the growing body of research, current studies often concentrate on specific AI techniques or quantum applications, lacking a unified framework that evaluates their practical effectiveness, scalability, and cost-efficiency. Addressing this gap, our survey systematically reviews and categorizes AI-driven methodologies across core aspects like system security, transmission speed, and reliability. Through a critical comparison and ranking of existing techniques, this study identifies best practices and key advancements while highlighting areas requiring further exploration. By providing an in-depth analysis of AI's potential to transform quantum communication, this paper aims to serve as a foundational resource for researchers and practitioners seeking to develop resilient, adaptive, and economically viable quantum communication systems.
Cyber-physical systems (CPSs) based on the Internet of Things (IoT) form the backbone of modern smart infrastructures, including smart cities, healthcare monitoring, industrial automation, and intelligent transportation. However, connecting many resource-limited IoT devices makes them more vulnerable to cyber threats, particularly quantum attacks. This review comprehensively examines quantum-secure communication (QSC) frameworks for IoT-enabled CPS, focusing on Quantum Key Distribution (QKD), post-quantum cryptographic (PQC) algorithms, and hybrid quantum–classical security models suitable for constrained devices. A PRISMA-guided search of the Scopus and Google Scholar database was conducted in January 2026 using three keyword groups related to hybrid security, artificial intelligence, and cyber-physical systems. Based on the evaluation, 6008 publications have been identified between 2001 and 2026. The first-round screening was performed for 4948 articles, after excluding duplicates. During the screening stage, 348 articles were selected for abstract scrutiny, 115 records were excluded due to no direct focus on CPS/IoT applications, 52 studies were excluded because these papers relied on traditional security models, 25 studies were excluded due to insufficient relevance to the review objectives, and 15 additional non-English studies were removed. Following the screening stage, 141 studies were selected for full-text eligibility. Out of those, 86 studies were removed due to a lack of specific evaluation metrics or not being published in a peer-reviewed venue. Furthermore, the publications are classified as QKD-based secure CPS and QSC for industrial IoT, AI-Assisted Secure Communication for CPS Networks, and hybrid PQC-QKD models for CPS/IoT devices. This article investigates recent advancements in secure data transmission, verified protocols, and AI-driven anomaly detection customized to CPS/IoT environments. In addition, operational hurdles, interaction with open innovations, real-time deployment, and secure edge-cloud integration are highlighted. By analyzing recent developments and identifying research gaps, this review provides a structured roadmap for designing secure, scalable, and quantum-safe IoT-based CPS frameworks capable of withstanding next-generation cyber threats. This systematic review was performed and reported according to the PRISMA 2020 guidelines.
Abstract The emerging era of quantum computing has highlighted the importance of secure communication systems that combine quantum-resistant cryptography, quantum communication, and advanced security analytics. This systematic review critically examines hybrid models of quantum and classical artificial intelligence, focusing on architectures for quantum key distribution (QKD), intrusion detection, network management, and the integration of post-quantum cryptography. Following PRISMA 2020 guidelines, studies from January 2020 to July 2026 were sourced from IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, Wiley Online Library, and backward citation searches. Out of these, 30 primary studies met the inclusion criteria and were evaluated using an eight-item quality rubric and a five-level evidence-maturity framework. The findings are grouped into three categories: AI-enhanced QKD and secure communication, hybrid quantum–classical learning for intrusion detection, and post-quantum or hybrid cryptographic solutions. AI-supported QKD research has shown notable reductions in parameter search time while maintaining near-optimal secret-key rates, primarily in simulation settings. Hybrid quantum machine learning models showed competitive intrusion detection accuracy and F1 scores, but improvements over classical methods were modest, dataset-dependent, and often lacked comprehensive reporting on false positives, statistical significance, or computational costs. Post-quantum cryptography approaches demonstrated greater maturity, with evaluations involving Transport Layer Security (TLS), Internet Protocol Security (IPsec), embedded devices, wireless links, and hardware accelerators, although performance varied with platform resources, cryptographic object sizes, network conditions, and side-channel protections. Among the studies, half were simulation-based, 30% involved laboratory experiments, and 20% were functional prototypes; none showed sustained operational deployment of an integrated hybrid quantum–classical AI security system. The review concludes that current evidence supports application-specific feasibility rather than universal quantum advantage. Achieving practical deployment requires standardized benchmarking, comparable classical baselines, transparent cost analysis, hardware validation, interoperable protocols, and longer-term field testing.
Quantum communications is a promising technology that will play a fundamental role in the design of future networks. In fact, significant efforts are being undertaken by both the quantum physics and the classical communications communities on developing new architectures, solutions, and practical implementations of quantum communication networks (QCNs). Although these efforts led to various advances in today's technologies, there still exists a non-trivial gap between the research efforts of the two communities on designing and optimizing the performance of QCNs. For instance, most prior works by the classical communications community ignore important quantum physics-based constraints when designing QCNs. For example, many existing works on entanglement distribution do not account for the decoherence of qubits inside quantum memories and, thus, their designs become impractical since they assume an infinite lifetime of quantum states. In this article, we bring forth a novel analysis of the performance of QCNs in a physics-informed manner, by relying on the quantum physics principles that underly the different components of QCNs. The need for the physics-informed approach is then assessed and its fundamental role in designing practical QCNs is analyzed across various open research areas. Moreover, we identify novel physics-informed performance metrics and controls that enable QCNs to leverage the state-of-theart advancements in quantum technologies to enhance their performance. Finally, we analyze multiple pressing challenges and open research directions in QCNs that must be treated using a physics-informed approach to lead practically viable results. Ultimately, this work attempts to bridge the gap between the classical communications and the quantum physics communities in the area of QCNs to foster the development of the future communication networks toward the quantum Internet.