This paper presents the third installment in a series reviewing contemporary solutions in quantum information technologies. Seven thematic areas are surveyed: (1) quantum control engineering, covering theoretical foundations, open-loop and feedback architectures, and industrial optimization use cases; (2) quantum radar, examining quantum illumination principles alongside the fundamental power and decoherence barriers to practical deployment; (3–4) the integration of quantum technologies with embedded systems and the Internet of Things, including quantum random number generators, nitrogen-vacancy magnetometers, miniaturized atomic clocks, and post-quantum cryptographic protocols such as QKD; (5) quantum simulation, contrasting analog and digital approaches with an emphasis on recent large-scale experiments demonstrating quantum utility; (6) quantum haptic interfaces for education, molecular simulation, and research visualization; and (7) quantum entanglement theory, tracing the path from the EPR paradox through Bell’s theorem to the 2022 Nobel Prize. Across these domains, the paper identifies recurring engineering challenges — particularly decoherence, scalability, and the transition from laboratory demonstrations to industrial deployment — and highlights the growing convergence of quantum physics with control theory, embedded computing, and applied engineering.
This paper presents the third installment in a series reviewing contemporary solutions in quantum information technologies. Seven thematic areas are surveyed: (1) quantum control engineering, covering theoretical foundations, open-loop and feedback architectures, and industrial optimization use cases; (2) quantum radar, examining quantum illumination principles alongside the fundamental power and decoherence barriers to practical deployment; (3–4) the integration of quantum technologies with embedded systems and the Internet of Things, including quantum random number generators, nitrogen-vacancy magnetometers, miniaturized atomic clocks, and post-quantum cryptographic protocols such as QKD; (5) quantum simulation, contrasting analog and digital approaches with an emphasis on recent large-scale experiments demonstrating quantum utility; (6) quantum haptic interfaces for education, molecular simulation, and research visualization; and (7) quantum entanglement theory, tracing the path from the EPR paradox through Bell’s theorem to the 2022 Nobel Prize. Across these domains, the paper identifies recurring engineering challenges — particularly decoherence, scalability, and the transition from laboratory demonstrations to industrial deployment — and highlights the growing convergence of quantum physics with control theory, embedded computing, and applied engineering.
Quantum communication and information technologies are poised to transform secure data transmission, distributed quantum computing, and scalable networking by leveraging fundamental principles such as superposition, entanglement, and the no-cloning theorem. This survey presents a structured overview of the quantum information processing (QIP) landscape, spanning theoretical foundations to system-level architectures. We cover quantum states, unitary evolution, gates, and channels, leading to the mathematical framework of quantum operations and the effects of decoherence. Quantum error correction (QEC) is examined through block codes and fault-tolerant operations, along with its integration with entanglement purification to address challenges of noisy intermediate-scale quantum (NISQ) devices. Physical platforms, including gate-based, continuousvariable and measurement-based models, are analyzed with an emphasis on error mitigation strategies to preserve coherence. We also discuss advancements in quantum sensing, particularly phase estimation, and evaluate communication protocols such as quantum key distribution (QKD) and teleportation in terms of fidelity, efficiency, and resilience. At the system level, components such as quantum networks, repeaters, and routers are reviewed with attention to scalability and security. Each section concludes with lessons learned, reflecting on challenges, trade-offs, and open questions. The survey culminates in outlining future directions in hybrid QEC-sensing integration, AI-enhanced error correction, and topological architectures, offering a forward-looking perspective on the co-evolution of quantum technologies. By bridging theory, protocols, physical systems, and architectures, this work charts a comprehensive roadmap toward secure, scalable, and high-fidelity quantum communication.
The article presents an overview of the quantum technologies across diverse domains. The exploitation of quantum phenomena—such as superposition, entanglement, and quantum interference—allows the introduction of practical and sometimes still theoretical innovations in a wide range of technologies that at some point met an insuperable obstacle in their development. The first part of the series of articles focuses on the influence of quantum information technologies on cryptography, computational physics, hardware, digital electronics, machine learning and healthcare applications. The seven sub-articles address both the opportunities and challenges of deploying quantum technologies.
Quantum computing represents a transformative approach to computation leveraging fundamental principles of quantum mechanics such as superposition, entanglement and interference to store and process information in ways that classical computers cannot achieve.This paper attempts to provide a bona fide bibliographic overview of the principles, computational models, hardware technologies, and potential applications of quantum computing.It analyses how quantum algorithms could outperform classical algorithms in cryptographic analysis, optimization, and big data analysis.The survey integrates viewpoints from recent works; it presents system architectures, software development challenges, and quantum-assisted applications in healthcare, artificial intelligence, cybersecurity, and industrial optimization.Meanwhile, it examines hybrid quantum-classical systems that would allow quantum technologies to be deployed in the near term skirted by the limitations currently posed by quantum hardware.Moreover, the paper discusses foremost hurdles in scaling, error-correction, and maintaining coherence.From reviewing the recent developments and whether possible, this present review work informs researchers, engineers, and practitioners alike on the current state, as well as on the long-run viability, of quantum computing.
This comprehensive review examines the latest advances in quantum technologies across three interconnected domains: quantum computing (NISQ devices, variational quantum algorithms, and quantum machine learning), quantum cryptography (NIST post-quantum cryptography standards, quantum key distribution, and advanced protocols like Quantum Permutation Pad), and quantum sensing (quantum dot-based sensors, NV-center magnetometry, atomic clocks, and energy applications). It highlights the convergence of these fields through quantum networks and distributed architectures while addressing key challenges such as decoherence, scalability, and error correction. An excellent resource for researchers seeking an integrated overview of quantum computing, security, and sensing developments (2020–2026).
Quantum computing has emerged as a transformative computational paradigm capable of addressing limitations increasingly encountered by classical computing systems as Moore’s law approaches physical and economic constraints. By leveraging quantum mechanical principles such as superposition, entanglement, and interference, quantum systems offer the potential for significant computational advantages in solving complex problems that are currently infeasible for conventional architectures. This review critically synthesizes recent advances in quantum computing by examining foundational principles, major algorithmic breakthroughs, evolving hardware platforms, and interdisciplinary real-world applications. A structured narrative literature review was conducted using major scientific databases, including PubMed, IEEE Xplore, Nature, ScienceDirect, and arXiv, with emphasis on peer-reviewed studies, landmark foundational research, and major industry developments published between 2018 and 2026. Key findings indicate substantial progress in superconducting, trapped ion, photonic, and topological quantum systems, alongside innovations in algorithms such as Shor’s, Grover’s, variational quantum methods, and quantum machine learning. Despite these advancements, major challenges including decoherence, noise, scalability limitations, and fault-tolerant error correction remain substantial barriers to commercial maturity. Future implications suggest quantum computing may profoundly influence artificial intelligence, cybersecurity, optimization, molecular simulation, and scientific discovery, particularly through hybrid classical-quantum systems and cloud-based democratization. Although practical deployment remains transitional, quantum computing is positioned to become a foundational technology with broad scientific, industrial, and societal implications.
Quantum technologies are moving from foundational science toward engineered systems in sensing and metrology, computing and simulation, communication and networking, and security. The transition is uneven in technological maturity: atomic clocks and several quantum sensors are operational; quantum key distribution has reached field deployment but remains constrained by integration, assurance and network architecture; post-quantum cryptography is entering standards-based migration; and general-purpose fault-tolerant quantum computing remains an engineering objective despite major progress in error correction. This treatise develops a mathematically grounded and application-oriented account of what quantum technologies are, what physical resources they exploit, what advantages have been proved or demonstrated, and where claims remain speculative. It distinguishes among scientific feasibility, engineering readiness, operational utility, economic value and societal legitimacy. Across fundamental physics, Earth and space sciences, environmental monitoring, health and life sciences, cybersecurity, critical infrastructure, hazards, defense, finance, decision support and AI-enabled systems, this work identifies bottlenecks and proposes a systems roadmap for robust, scalable, efficient, verifiable and responsible quantum-enabled capabilities.