The second (quantum computing algorithms and HW-computers) and third quantum (quantum programming and SW-engineering and quantum “powerful” computing AI) revolutions have led to the necessity in developing of intelligent SW/HW platform (strong quantum computational AI) of industrial quantum technologies for mega - science projects “Industry 5.0 / 6.0”. This fact, in turn, has raised the big challenge of training a new generation of quantum engineering staff in the fields of quantum end-to-end IT, quantum software engineering and quantum intelligent control. The creation of an appropriate software-algorithmic platform and hardware support in view of a quantum computer for industrial development required a radical revision of the foundations of educational processes for quantum engineering, the creation of a new technological structure and mathematical / physical / technical background in dynamically developing areas of application of quantum end-to-end IT. The lack of teaching staff and objective assessments of the necessity of industry and science for quantum engineering personnel only increased the difficulties in the development of quantum engineering. There is a certain mathematical maturity required to understand the quantum mechanics of finite dimensional systems. We review only the basics here and this is mostly to familiarize the reader with the notation used for the remainder of this Introduction.
The second (quantum computing algorithms and HW-computers) and third quantum (quantum programming and SW-engineering and quantum “powerful” computing AI) revolutions have led to the necessity in developing of intelligent SW/HW platform (strong quantum computational AI) of industrial quantum technologies for mega - science projects “Industry 5.0 / 6.0”. This fact, in turn, has raised the big challenge of training a new generation of quantum engineering staff in the fields of quantum end-to-end IT, quantum software engineering and quantum intelligent control. The creation of an appropriate software-algorithmic platform and hardware support in view of a quantum computer for industrial development required a radical revision of the foundations of educational processes for quantum engineering, the creation of a new technological structure and mathematical / physical / technical background in dynamically developing areas of application of quantum end-to-end IT. The lack of teaching staff and objective assessments of the necessity of industry and science for quantum engineering personnel only increased the difficulties in the development of quantum engineering. There is a certain mathematical maturity required to understand the quantum mechanics of finite dimensional systems. We review only the basics here and this is mostly to familiarize the reader with the notation used for the remainder of this Introduction.
Principles and methodologies of quantum algorithmic gates design for master course and PhD students in computer science, control engineering and intelligent robotics described. The possibilities of quantum algorithmic gates simulation on classical computers discussed. Applications of quantum gate of nanotechnology in intelligent quantum control introduced. Anew approach to a circuit implementation design of quantum algorithm gates for fast quantum massive parallel computing presented. The main attention focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference, which are in general time-consuming operations due to the number of products that have performed. SW & HW support sophisticated smart toolkit of supercomputing accelerator of quantum algorithm simulation on small quantum programmable computer algorithm gate (that can program in SW to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates) described. As example, the method for performing Grover’s interference operator without product operations introduced. The background of developed information technology is the "Quantum / Soft Computing Optimizer" (QSCOptKBTM) SW based on soft and quantum computational intelligence toolkit.
From the point view of quantum IT engineering, the definition of the concept and issues of intelligent control of weakly structured and poorly formalized objects with underdetermined/hidden parameters are discussed. The stages of domestic quantum IT software engineering for the design of embedded self-organizing intelligent control systems using the QSCIT (Quantum Soft Computational Intelligence Toolkit) software toolkit are presented. QSCIT is based on industrial knowledge base optimizers (SC&QC)OptKBTM and employs quantum soft computing technologies. A new type of coordinated dual-channel intelligent control of nitrogen pressure and flow valves with hidden feedback is considered in a process with a variable superconducting magnet cooling structure. In this case, the superconducting magnet is considered as a classical control object with a weakly structured, poorly formalized model with underdetermined parameters, information about which is contained in the learning signal measured on the actual object. Quantum technology for studying a highly nonlinear and dynamically unstable autonomous intelligent robot forms the basis of a system simulating the interaction of nitrogen pressure and flow valves, as well as an intelligent self-organizing quantum controller coordinating the control of nitrogen pressure and flow valves in a cryogenic superconducting magnet cooling unit in the NICA mega-science project (JINR). Quantum soft computing and quantum fuzzy inference in the quantum controller structure extract knowledge from the learning signal and, based on the extracted amount of hidden quantum information, generate additional "thermodynamic" control power as an additional information resource for the intelligent controller to perform useful work. These processes are implemented on a classical processor. The generation of this additional information resource is possible due to the existence (experimentally proven in the study) of a quantum synergistic effect of self-organization of imprecise knowledge bases: from a finite number of imprecise knowledge bases, quantum fuzzy inference generates a robust knowledge base in real time. An entropy analysis of the controllers' operation demonstrated the rational use of useful resources by the quantum intelligent controller, necessary to guarantee the achievement of the control goal. The efficiency and quantum advantage of using intelligent self-organizing quantum controllers (embedded in onboard intelligent control systems) to control classical control objects based on quantum soft computing technologies are demonstrated.
Currently, quantum technologies are the driving force behind technological progress (Industry 4.0/5.0/6.0 or Society 6.0). The development of quantum information technologies gives rise to new quantum threats to information security. The requirements of the federal project “Personnel for the Digital Economy or the Data Economy” for the key information technology – “Quantum Technologies” (Priority 1) – can be fulfilled only by developing an appropriate training system for engineering and scientific personnel in the fields of quantum information technologies, quantum robust artificial intelligence and quantum resilience. The creation of a vertically integrated education system, which includes not only basic higher education, but also the training of scientific personnel and upskilling for already employed professionals, will contribute to the development of innovative technologies in general. The paper presents the results of joint efforts of the Sirius University of Science and Technology together with the Quantum Consortium of Business and Universities to train personnel in the sphere of quantum information technologies for the development of such an education system.
Quantum technology is developing so quickly, that there has been intense research for quantum technologies in both academia and industry in recent years.Documents and literature have been created in vast quantities as the capability of quantum computers continues to increase.After an informative introduction and a summary of key achievements and current advancements in the field of quantum computing.The second phase of the quantum revolution known as continuous research and innovation in the hardware, software, and applications of quantum computers further explained.Quantum computing has long theoretical roots, but in recent years, with the development of useful tools and technologies, the research has moved from theory to reality in Quantum Computers, Quantum Networks, Quantum Cryptography, and Quantum Machine Learning.A framework is presented for creating a quantum engineering education program that will satisfy the demands of both academics and research institutions in the world.The Control, electronics, nanofabrication, cryogenic and solid-state technologies, optics, atoms and ions, and a plan for quantum engineering fields that presents an excellent set of opportunities for education research are all used to outline a hands-on training on quantum hardware software and applications.
Abstract Quantum computing leverages fundamental quantum-mechanical phenomena—most notably superposition, entanglement, and quantum tunneling—to perform computations in ways that differ fundamentally from classical digital processing. Compared to conventional computing architectures, quantum systems promise significant reductions in computational time and potentially lower energy consumption for specific classes of problems. These advantages, combined with advances in nanoscale engineering and the slowing of traditional hardware scaling trends such as Moore’s Law, have led to substantial commercial and national-security-driven investments in quantum technologies over the past decade. A major milestone was reached when Google announced the experimental demonstration of “quantum supremacy,” showing that a quantum processor could execute a specific computational task infeasible for a classical supercomputer within practical time constraints. Although the demonstrated problem had no immediate practical application, this achievement marked a crucial step toward the development of quantum systems capable of delivering real-world computational advantages and provided a more precise technical framing of the concept of quantum advantage. Despite the fact that the mathematical foundations, programming models, and principal quantum algorithms were established in the 1990s, quantum computing remained largely confined to a specialized research community for decades. Today, the increasing accessibility of cloud-based quantum hardware calls for a broader dissemination of implementation-oriented knowledge among researchers and practitioners in computer science, software engineering, and related fields. The quantum programming paradigm differs fundamentally from classical programming models and often relies on physical and algebraic notations that may pose barriers to traditionally trained computer scientists. This series of articles provides a self-contained and concise introduction to quantum computing and its core algorithms, with a strong emphasis on practical implementation. Given that real quantum processors—such as those accessible via the IBM quantum ecosystem—are now available as cloud services, experimental validation can be conducted both on simulators and on actual hardware for small-scale inputs. While other platforms such as Rigetti and IonQ also offer cloud-based quantum computing services, this review focuses exclusively on the IBM quantum computing ecosystem.
Quantum Computing The twenty-first century has witnessed remarkable advancements in computing technologies, transforming every aspect of modern society. As conventional computing systems approach their physical and computational limits, the search for new paradigms capable of solving increasingly complex problems has led to the emergence of Quantum Computing. By harnessing the principles of quantum mechanics, quantum computing represents a revolutionary approach that has the potential to redefine computation, communication, and information processing on an unprecedented scale. Quantum Computing is designed to provide readers with a comprehensive understanding of the concepts, principles, technologies, and applications that form the foundation of this rapidly evolving field. This book aims to bridge the gap between theoretical quantum mechanics and practical computational applications, enabling students, researchers, academicians, and professionals to explore the transformative potential of quantum technologies. The chapters in this book cover a broad spectrum of topics, including the fundamentals of quantum mechanics, quantum bits (qubits), quantum gates, superposition, entanglement, quantum circuits, quantum algorithms, quantum cryptography, quantum communication, and quantum error correction. The book also explores the architecture of quantum computers and examines the challenges involved in building scalable and fault-tolerant quantum systems. As industries increasingly seek innovative solutions to complex computational problems, quantum computing is emerging as a promising technology with applications in cryptography, artificial intelligence, machine learning, optimization, financial modeling, healthcare, pharmaceutical research, materials science, logistics, and climate modeling. The ability of quantum computers to process vast amounts of information simultaneously offers opportunities that were previously beyond the reach of classical computing systems. Special attention has been given to contemporary developments in quantum technologies, including quantum supremacy, hybrid quantum-classical computing, cloud-based quantum platforms, and the growing role of quantum computing in scientific discovery and industrial innovation. The book also discusses ethical, security, and societal implications associated with the advancement of quantum technologies. The primary objective of this book is to equip readers with both foundational knowledge and practical insights into the field of quantum computing. Through a balanced presentation of theory, applications, case studies, and emerging research trends, the book seeks to inspire curiosity, innovation, and further exploration in this transformative domain. We extend our sincere gratitude to the authors, reviewers, researchers, academicians, and industry experts whose valuable contributions have enriched the quality and relevance of this publication. Their dedication and expertise have helped create a resource that reflects the latest developments and future possibilities of quantum computing. We hope that Quantum Computing will serve as a valuable guide for students, educators, researchers, and technology professionals seeking to understand the next frontier of computational science. May this book inspire new ideas, foster innovation, and contribute to the advancement of knowledge in one of the most exciting technological revolutions of our time. Mr. M. Rajeshkumar Dr. R. Mariappan Mr. E.Janakiraman,