Quantum networks are connections between quantum processors and repeaters that produce, exchange, and process quantum information. They serve to optimize the transmission of data in the form of quantum bits, known as qubits. Quantum networks were developed to complement classical networks in order to solve problems currently considered impossible. Among these applications are quantum key distribution (QKD), clock synchronization, secure remote computing, metrology, and distributed consensus. The objective of this work is to investigate the technological foundations, their strategic applications, and consequences in geopolitics. Specifically, this article addresses applications in energy sectors considered strategic, such as oil and gas and nuclear energy. Combined with Artificial Intelligence (AI), this technology can accelerate the discovery of wells and the processing of company analyses, making carbon capture more efficient. In nuclear reactors, quantum computing represents a significant advance. Its advantage lies in its ability to perform more precise simulations of nuclear reactions, for example, neutron scattering, fission and fusion processes, and the exploration of extreme environments that are difficult or impossible to reproduce in the laboratory. Furthermore, this article also analyzes the geopolitical impact of this scenario, emphasizing the technological race and strategic disputes. Next, the challenges and perspectives regarding technical barriers, regulatory issues, and the future of quantum networks in the energy matrix are discussed. To conclude this work, reflections are made on methods to achieve the safe and ethical integration of these quantum technologies.
Quantum networks are connections between quantum processors and repeaters that produce, exchange, and process quantum information. They serve to optimize the transmission of data in the form of quantum bits, known as qubits. Quantum networks were developed to complement classical networks in order to solve problems currently considered impossible. Among these applications are quantum key distribution (QKD), clock synchronization, secure remote computing, metrology, and distributed consensus. The objective of this work is to investigate the technological foundations, their strategic applications, and consequences in geopolitics. Specifically, this article addresses applications in energy sectors considered strategic, such as oil and gas and nuclear energy. Combined with Artificial Intelligence (AI), this technology can accelerate the discovery of wells and the processing of company analyses, making carbon capture more efficient. In nuclear reactors, quantum computing represents a significant advance. Its advantage lies in its ability to perform more precise simulations of nuclear reactions, for example, neutron scattering, fission and fusion processes, and the exploration of extreme environments that are difficult or impossible to reproduce in the laboratory. Furthermore, this article also analyzes the geopolitical impact of this scenario, emphasizing the technological race and strategic disputes. Next, the challenges and perspectives regarding technical barriers, regulatory issues, and the future of quantum networks in the energy matrix are discussed. To conclude this work, reflections are made on methods to achieve the safe and ethical integration of these quantum technologies.
Quantum networks are connections between quantum processors and repeaters that produce, exchange, and process quantum information. They serve to optimize the transmission of data in the form of quantum bits, known as qubits. Quantum networks were developed to complement classical networks in order to solve problems currently considered impossible. Among these applications are quantum key distribution (QKD), clock synchronization, secure remote computing, metrology, and distributed consensus. The objective of this work is to investigate the technological foundations, their strategic applications, and consequences in geopolitics. Specifically, this article addresses applications in energy sectors considered strategic, such as oil and gas and nuclear energy. Combined with Artificial Intelligence (AI), this technology can accelerate the discovery of wells and the processing of company analyses, making carbon capture more efficient. In nuclear reactors, quantum computing represents a significant advance. Its advantage lies in its ability to perform more precise simulations of nuclear reactions, for example, neutron scattering, fission and fusion processes, and the exploration of extreme environments that are difficult or impossible to reproduce in the laboratory. Furthermore, this article also analyzes the geopolitical impact of this scenario, emphasizing the technological race and strategic disputes. Next, the challenges and perspectives regarding technical barriers, regulatory issues, and the future of quantum networks in the energy matrix are discussed. To conclude this work, reflections are made on methods to achieve the safe and ethical integration of these quantum technologies.
By enhancing computational capabilities, data processing rates, and decision-making accuracy, the integration of AI and quantum networks has the potential to significantly enhance organisational performance.Quantum networks are an exceptional foundation for artificial intelligence applications because they enable rapid communication and guarantee the secure transfer of data. The objective of this investigation is to evaluate the advantages and disadvantages of integrating quantum networks with artificial intelligence (AI). It also intends to investigate the potential effects of this integration on various sectors, including strategic planning, operations, and customer service. The research endeavours to offer a glimpse into the potential future challenges that may result from this combination. The current advancements in the sector are assessed in this article, and case studies are provided to demonstrate the substantial transformation that these technologies can bring to firms by improving efficiency, promoting creativity, and obtaining a competitive advantage.
Quantum computing is a new technological discovery that has the potential to transform industries based on high computational capabilities. This work explores how quantum computing will be integrated into AI applications and what impacts it will have on IT networks. A review of the recent literature shows that IT networks need to be upgraded to receive quantum-enhanced AI algorithms, as they require more computation power and faster real-time processing. It covers three major topics: the enabling of quantum AI applications, the role of QRC (quantum reservoir computing) in IT networking, and the challenges concerning the protocols of quantum communication, such as QKD (quantum key distribution). Network architectures of today’s state of the art will have to evolve toward enabling quantum-enabled AI, primarily regarding processing speed and interaction between the quantum and classical systems. This work, therefore, wishes to explain how such technological advances could influence AI applications and tune IT networks. We discuss the following questions: How can IT networks support the exploitation of quantum computing for AI applications? What effects do the dynamics and symmetries of quantum reservoir computing have on IT networks? Which IT networks can adapt to the challenges introduced by quantum computing technologies? The scope and depth of contributions reviewed in the articles together suggest huge potential for quantum computing in optimizing machine learning processes and IT networks with improved data handling and network management. At the same time, these ambitions are underlined by scaling concerns related to quantum hardware and qubit stabilization, and finally, the relative easiness with which quantum-classical computing is retrofitted into existing IT infrastructures. The findings suggest that hybrid quantum-classical systems will be essential in future IT infrastructure; efficiency and scalability will have to balance with security concerns in quantum computing environments.
Abstract The energy sector is expected to undergo significant changes in the coming decades with the advent of new technologies, including smart grid development, microgrid expansion, increasing electric vehicle and renewable energy usage, and enhanced measures to minimize greenhouse gas emission, among others. In tandem, these changes are expected to create new opportunities for the deployment of quantum technologies within the energy sector. Building on the authors' previous reviews on the current state of and future opportunities for quantum sensing, quantum computing and quantum simulations for energy sector applications, this work provides an overview of recent progress in quantum networking and communications for the energy industry, with a focus on platforms, devices, and protocols, including quantum teleportation and quantum key distribution. Specific areas of relevance to the energy sector are then analyzed, including the role of quantum networks for greenhouse gas monitoring, secure data collection and transmission in smart grids, nuclear power plants’ safety, facilitating oil and gas exploration, and other energy‐relevant applications. This review concludes with a brief overview of areas for future innovation, including the need for platforms for simulating quantum networks, quantum material and platform design, and computational approaches to accelerate quantum protocol discovery and development.
Quantum computing represents a transformative shift from classical computational paradigms by utilizing quantum mechanical principles such as superposition, entanglement, and quantum interference.In the era of Artificial Intelligence (AI), the integration of quantum computing with information technology opens new possibilities for solving complex computational problems beyond the capabilities of traditional systems.This paper explores the conceptual foundations of quantum computing and its convergence with AI-driven information technologies.It examines how quantum algorithms enhance machine learning efficiency, optimize large-scale data processing, and strengthen cybersecurity through quantum cryptography.Furthermore, the study discusses current technological challenges including hardware instability, error correction, scalability issues, and the need for interdisciplinary expertise.Using analytical and secondary data sources, the paper evaluates emerging applications in healthcare, finance, communication networks, and scientific simulations.The research concludes that quantum-AI integration will redefine computational intelligence, enabling faster decision-making and innovative technological solutions.The study highlights future research directions and emphasizes the importance of national-level academic collaboration to accelerate quantum technology adoption.
Quantum technologies are rapidly emerging as a transformative force with profound implications for critical infrastructures, national security, and global governance. Quantum computing, quantum communications, and quantum sensing promise unprecedented advances in data processing, secure communications, and environmental and infrastructure monitoring. At the same time, their disruptive potential introduces new ethical, security, and geopolitical risks, particularly for systems that underpin modern societies such as energy networks, telecommunications, finance, transportation, and defence infrastructures. This paper examines the governance of quantum technologies for critical infrastructures, moving from ethical impact assessment to the formulation of coherent national strategies. The study argues that the unique characteristics of quantum technologies — including their high degree of complexity, dual-use nature, and capacity to undermine existing cryptographic and security frameworks — require a shift from reactive regulation to anticipatory and responsible governance. Traditional regulatory approaches are insufficient to address the speed, uncertainty, and strategic relevance of quantum innovation. Instead, the paper emphasizes the need to integrate ethical impact assessment, risk analysis, and societal considerations at the earliest stages of research, development, and deployment. Ethical governance is presented not as a constraint on innovation, but as a foundational element for ensuring trust, resilience, and long-term sustainability. The analysis situates quantum governance within a broader geopolitical context, highlighting how major global actors are investing in quantum capabilities as strategic assets. This competition increases the urgency for coordinated governance frameworks that balance technological sovereignty, security, and international cooperation. Particular attention is given to the protection of critical infrastructures and the transition towards quantum-safe systems, especially in the field of cybersecurity and secure communications. Finally, the paper outlines the implications for national and European strategies, stressing the importance of multi-level governance involving governments, international organisations, industry, and research institutions. It concludes that only a holistic approach — combining ethical foresight, anticipatory governance, and strategic planning — can ensure that quantum technologies enhance societal resilience and security rather than exacerbate systemic vulnerabilities. In this sense, quantum governance becomes a central component of future national strategies for critical infrastructure protection and technological leadership.