Quantum computing is an emerging paradigm that exploits principles of quantum mechanics—such as superposition, entanglement, and tunneling—to process information in ways that classical computers cannot. Rapid progress in quantum hardware, quantum algorithms, and error-correction research suggests transformative potential across fields such as cryptography, optimization, materials science, and machine learning. This review summarizes fundamental concepts, leading hardware platforms, algorithmic milestones, current challenges, and future trajectories in the development of large-scale, fault-tolerant quantum computers.
Quantum computing is an emerging paradigm that exploits principles of quantum mechanics—such as superposition, entanglement, and tunneling—to process information in ways that classical computers cannot. Rapid progress in quantum hardware, quantum algorithms, and error-correction research suggests transformative potential across fields such as cryptography, optimization, materials science, and machine learning. This review summarizes fundamental concepts, leading hardware platforms, algorithmic milestones, current challenges, and future trajectories in the development of large-scale, fault-tolerant quantum computers.
Quantum computing represents a transformative paradigm that exploits the principles of quantum mechanics—superposition, entanglement, and quantum interference—to perform computations beyond the capabilities of classical computers. This review presents a comprehensive overview of the fundamental concepts underlying quantum computation, including qubits, quantum gates, quantum algorithms and measurement theory. It further examines major physical implementations of quantum computers, such as superconducting circuits, trapped ions, photonic systems, spin-based qubits, and topological approaches, highlighting their operational principles, advantages, and technological limitations. Key challenges hindering large-scale quantum computation—decoherence, error rates, qubit scalability, and fault tolerance—are critically discussed. Additionally, recent progress in quantum error correction, hybrid quantum–classical algorithms, and hardware optimization is summarized. The review concludes by outlining future research directions and potential applications of quantum computing in cryptography, materials science, optimization, and drug discovery. By integrating theoretical foundations with experimental advancements, this article aims to provide a clear and accessible reference for students, researchers, and scientists entering the rapidly evolving field of quantum computing.
Quantum computing is an emerging paradigm that leverages the principles of quantum mechanics to solve computational problems beyond the reach of classical computers. This article provides an overview of the fundamental concepts of qubits, the distinctive features of quantum mechanics such as superposition and entanglement, and the challenges of building scalable, fault-tolerant systems. It surveys key quantum algorithms and their potential applications in fields including cryptography, optimization, finance, chemistry, and machine learning. Additionally, it highlights the importance of verification frameworks for ensuring the reliability of quantum programs. A literature review of significant contributions is presented, drawing insights from recent surveys on quantum algorithms, qubit technologies, and software verification approaches. The article concludes by discussing ongoing challenges, such as error correction overhead, hardware scalability, and verification complexity, and suggests directions for future research.
Quantum computing leverages quantum mechanical concepts, including superposition, entanglement, and interference, to solve problems that traditional computers cannot handle efficiently. This study presents a comprehensive overview of the field, covering both the theoretical foundations and the latest developments in quantum hardware and algorithms. This study covers fundamental elements, qubits, gates, and circuits while emphasizing quantum parallelism as a distinctive feature. To illustrate efficiency gains, we explore notable algorithms like Shor’s factorization procedure and Grover’s search algorithm. Furthermore, we analyze recent advancements in quantum hardware, focusing on superconducting qubits, trapped ions, and photonic quantum computers, with an emphasis on implementations by IBM, Google, and other industry leaders. The discussion also addresses major challenges such as decoherence, noise, and the need for quantum error correction to achieve fault tolerance. Finally, we explore emerging applications in cryptography, optimization, quantum machine learning, and material simulation, and identify critical open problems that must be addressed to realize scalable, universal quantum computing. Our review underscores the transformative potential of quantum technologies across science and industry.
Quantum computing represents a new paradigm in computation that exploits the principles of quantum mechanics to solve complex problems beyond the practical capabilities of classical computers. By utilizing qubits, superposition, entanglement, and quantum interference, quantum computers have the potential to revolutionize cryptography, optimization, drug discovery, artificial intelligence, financial modeling, and materials science. Although remarkable progress has been achieved in quantum hardware and algorithms, significant challenges remain, including qubit stability, error correction, scalability, high implementation costs, and limited practical applications. This paper presents the fundamental principles of quantum computing, explores its major applications, examines current limitations, and discusses future research directions.
Quantum technology has recently emerged as a transformative computing paradigm. It is based on fundamental principles of quantum mechanics such as superposition, interference, and entanglement. This technology executes high computations that are impracticable by traditional computers. In recent years, developments in quantum technologies i.e algorithms, machine learning, cryptography, hardware design, and hybrid quantum classical frameworks have accelerated research and industrial interest. This paper provides a comprehensive review of quantum computing. It covers fundamental concepts, mathematical foundations, quantum algorithms, hardware platforms. It also focusses important applications, challenges, and emerging trends. The paper concludes with future research directions & the transformative potential of quantum technologies in computing, cryptography, optimization, and artificial intelligence.
Quantum computing, grounded in the principles of superposition and entanglement, has emerged as a revolutionary paradigm with the potential to outperform classical systems in specific computational tasks. This paper presents a comprehensive survey of the foundational concepts, algorithmic developments, hardware architectures, and programming ecosystems in quantum computing. We analyze the current progress in key application areas such as cryptography, machine learning, optimization, and quantum chemistry. Furthermore, we review recent advances between 2023 and 2025, including developments in fault-tolerant architectures and quantum error correction. The paper also discusses the significant technical challenges that hinder large-scale practical deployment, including qubit scalability, decoherence, and programming limitations. By synthesizing literature across disciplines, this review aims to provide a holistic understanding of the quantum computing landscape and outline critical directions for future research and integration with classical systems.