Superposition, entanglement, and interference are the key characteristics of quantum computing that can provide exponential speedups compared to classical computing. This chapter offers a thorough survey of the latest developments in technology that propel quantum computing from the theory to the reality. It examines prominent hardware platforms including superconducting qubits, trapped-ion systems, photonic computing, and topological approaches, as well as developments in quantum algorithms, error correction and fault resilience architectures. Further, the chapter discusses quantum-classical integrated methods for the Noisy Intermediate-Scale Quantum (NISQ) era and how secure communications, cloud computing, and artificial intelligence can be coupled with quantum computing. Practical implementation into healthcare, finance, cyber security and logistics sectors are discussed. Finally, the chapter highlights the challenges and future directions needed to realize scalable and viable quantum systems.
Superposition, entanglement, and interference are the key characteristics of quantum computing that can provide exponential speedups compared to classical computing. This chapter offers a thorough survey of the latest developments in technology that propel quantum computing from the theory to the reality. It examines prominent hardware platforms including superconducting qubits, trapped-ion systems, photonic computing, and topological approaches, as well as developments in quantum algorithms, error correction and fault resilience architectures. Further, the chapter discusses quantum-classical integrated methods for the Noisy Intermediate-Scale Quantum (NISQ) era and how secure communications, cloud computing, and artificial intelligence can be coupled with quantum computing. Practical implementation into healthcare, finance, cyber security and logistics sectors are discussed. Finally, the chapter highlights the challenges and future directions needed to realize scalable and viable quantum systems.
Quantum computing has emerged as a paradigm-shifting computational model capable of addressing problems intractable for classical systems. This chapter explores the foundational principles, hardware implementations, and algorithmic approaches that define the field of quantum computing. Key quantum mechanical phenomena – such as superposition, entanglement, and interference – are examined in relation to their computational applications. The discussion extends to qubit realization technologies including superconducting circuits, trapped ions, photonic systems, and emerging platforms like topological qubits. Core quantum algorithms, including Shor’s and Grover’s, are analyzed to demonstrate their operational mechanics and performance advantages. The chapter also presents current challenges in quantum error correction, coherence preservation, and hardware scalability, particularly in the context of noisy intermediate-scale quantum devices. Further, it highlights applications across domains such as cryptography, optimization, quantum chemistry, and machine learning. The content is supported by illustrative diagrams, comparative tables, and up-to-date research references, providing a comprehensive overview of the state of quantum computing and its future directions.
Quantum computing continues to make great progress, impacting not only the theory of computer science but also technological innovations. This chapter gives an overview of the subject matter, presenting the current state-of-the-art in qubit architectures, quantum algorithms, hardware achievements made since 2019 through 2024, potential applications, and difficulties ahead for wide-scale implementation. Utilizing the latest results of research and innovation efforts conducted by top industry leaders, the chapter covers topics such as the comparison of superconducting, trapped ion, neutral atom, photonic, and topological qubits, quantum algorithms, applicability in various industries like cryptography, optimization, material sciences, and artificial intelligence, and the advancement of quantum error correction and fault-tolerant computing. Finally, the chapter takes a closer look at prevalent myths associated with near-term quantum advantage and focuses on true developments in quantum hardware and logical qubits.
Quantum computing is an emerging form of computing that uses the rules of quantum physics to process information in ways that are far different from how computers do it now. Quantum computing uses quantum bits, or qubits, which can exist in superpositions of states and get entangled with each other, which is different from classical computing, which uses a bit that represents binary values (0 or 1). These characteristics allow quantum devices to execute parallel computations, enabling significant speedups for specific categories of problems considered intractable for classical machines. This chapter gives a thorough introduction to quantum computing, starting with a historical overview of its foundations in quantum physics and significant theoretical advancements. It analyzes fundamental ideas including superposition, entanglement, quantum interference, and the no-cloning theorem, explaining how these elements distinguish quantum computation from traditional approaches. The advancement of quantum hardware is examined through several architectures, trapped ions, superconducting circuits, photonics, and topological qubits, together with software frameworks like Qiskit, Cirq, and PennyLane, which support algorithm development and simulation. The chapter examines fundamental quantum algorithms, such as Grover’s algorithm for database search, Shor’s algorithm for integer factorization, and hybrid variational methods designed for noisy intermediate-scale quantum devices. The practical applications in domains including as encryption, optimization, machine learning, chemistry, and finance emphasize the real-world significance of quantum technology. Challenges like decoherence, noise, scalability, and algorithmic maturity are rigorously analyzed, followed by an anticipated discourse on future trajectories including fault-tolerant architectures, quantum networking, and the development of quantum cloud services. This chapter presents a fundamental introduction for students, researchers, and practitioners seeking to comprehend the essential principles, functionalities, and possibilities of quantum computing in the post–Moore’s law period.
This paper presents a comprehensive review of quantum computing and the technological foundations of quantum processors. Quantum computing represents a transformative computational paradigm that leverages the fundamental principles of quantum mechanics—such as superposition, entanglement, and quantum interference—to solve complex problems that are intractable for classical computers. At the core of this paradigm lies the quantum processor, a specialized hardware system designed to initialize, control, and measure quantum bits (qubits) through precise gate operations and coherent interactions. The survey examines the essential theoretical concepts underlying quantum computation and provides a structured comparison of leading quantum processor platforms. Prominent architectures, including superconducting circuits, trapped-ion systems, and photonic implementations, are analyzed in terms of their physical mechanisms, scalability, coherence properties, and engineering challenges. Each platform offers distinct advantages and faces specific technical limitations related to noise, error correction, and fabrication complexity. In addition to reviewing hardware developments, this study highlights key obstacles in advancing quantum processors toward large-scale, fault-tolerant systems. Issues such as qubit stability, error mitigation, thermal management, and system integration are discussed to present a realistic perspective on current progress. Performance indicators including gate fidelity, coherence time, connectivity, and scalability are used to compare architectural approaches. The objective of this paper is to provide a clear and organized synthesis of recent advancements in quantum computing hardware, thereby offering researchers and practitioners a foundational reference to support continued innovation and development in this rapidly evolving field.
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 computing has transitioned from a theoretical curiosity to an emerging technological paradigm with demonstrable computational advantages in specific problem domains. This paper presents a comprehensive review of current advances in quantum computing hardware, software, and near-term applications within the Noisy Intermediate-Scale Quantum (NISQ) era. We examine the architectural evolution of leading quantum platforms, including superconducting, trapped-ion, and photonic systems, analyzing their qubit counts, gate fidelities, and coherence times. The paper evaluates key quantum algorithms Shor's factoring algorithm [1], Grover's search algorithm [2], the Variational Quantum Eigensolver (VQE) [3], and the Quantum Approximate Optimization Algorithm (QAOA) [4] in the context of their practical applicability to real-world problems. We further discuss the milestone of quantum computational advantage demonstrated by Google's Sycamore processor [5] and IBM's ambitious hardware roadmap toward fault-tolerant quantum computing [6]. Our analysis reveals that while universal fault-tolerant quantum computing remains a long-term objective, NISQ-era devices are already yielding valuable results in quantum chemistry simulation, combinatorial optimization, and quantum machine learning. We conclude by identifying the critical challenges—error correction, scalability, and algorithm design that must be addressed to realize the full potential of quantum computing.