Quantum computing is at the cutting edge of technological innovation, with the potential to transform a wide array of scientific and practical fields. This literature survey addresses the critical need for a structured understanding of recent advancements and identifies research gaps. It comprehensively reviews recent advancements in quantum computing, emphasizing non-standard architectures, applications in material sciences, and the integration of quantum and classical machine learning models. The survey also examines quantum algorithms for real-time systems, explores cryptographic protocols beyond Shor's algorithm, and discusses resource management in cloud computing. Key findings highlight significant progress in algorithm efficiency, practical applications in 2D materials and topological insulators, and the hybridization of quantum and classical models. Challenges such as scalability, resource optimization, and ethical concerns still remain. This paper guides future research to focus on optimizing algorithms, efficient resource allocation, and enhancing security measures. This work synthesizes current knowledge, guiding future research efforts and contributing to the advancement of the quantum computing research community.
Quantum computing is at the cutting edge of technological innovation, with the potential to transform a wide array of scientific and practical fields. This literature survey addresses the critical need for a structured understanding of recent advancements and identifies research gaps. It comprehensively reviews recent advancements in quantum computing, emphasizing non-standard architectures, applications in material sciences, and the integration of quantum and classical machine learning models. The survey also examines quantum algorithms for real-time systems, explores cryptographic protocols beyond Shor's algorithm, and discusses resource management in cloud computing. Key findings highlight significant progress in algorithm efficiency, practical applications in 2D materials and topological insulators, and the hybridization of quantum and classical models. Challenges such as scalability, resource optimization, and ethical concerns still remain. This paper guides future research to focus on optimizing algorithms, efficient resource allocation, and enhancing security measures. This work synthesizes current knowledge, guiding future research efforts and contributing to the advancement of the quantum computing research community.
Quantum computing represents a transformative shift in computational paradigms, offering unprecedented potential for solving complex problems beyond the reach of classical computers. This paper explores the theoretical foundations of quantum computing, including quantum bits (qubits), superposition, entanglement, and quantum gates, and examines their implications for computation. Utilizing a qualitative approach, this study conducts a comprehensive literature review and library research to analyze the current state of quantum computing technology, its applications, and the challenges it faces in practical implementation. The findings reveal significant advancements in quantum algorithms, such as Shor's and Grover's algorithms, which demonstrate the capability of quantum computing to revolutionize fields like cryptography, optimization, and materials science. However, the research also highlights the technical challenges, including qubit stability, error correction, and scalability, which must be addressed to transition from theoretical models to practical applications. Additionally, the study discusses the ethical and societal implications of quantum computing, particularly in relation to data security and privacy. The paper concludes by outlining future research directions and potential real-world applications, emphasizing the need for interdisciplinary collaboration to fully realize the potential of quantum computing in solving some of the most pressing global challenges.
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, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.
Quantum computing represents a paradigm shift in computational capabilities, promising to solve problems that are intractable for classical computers. This paper explores the architecture, implementation, and operational aspects of quantum computing, focusing on its applications in various fields. I conducted a comprehensive literature review to identify existing research gaps and propose methodologies for effective quantum computing implementation. My findings highlight the potential of quantum computing in optimization, cryptography, and machine learning, among other areas. This research paper provides a comprehensive examination of the architecture, implementation, and operational strategies of quantum computing, with a focus on its diverse applications in optimization, cryptography, and machine learning. Through an extensive literature review, I identify critical research gaps and propose innovative methodologies for effective quantum computing implementation. I conclude with strategic recommendations for future research directions, emphasizing the importance of enhancing quantum hardware, developing hybrid algorithms, and fostering interdisciplinary collaborations. This foundational study not only deepens the understanding of quantum computing’s current state but also paves the way for future advancements in this rapidly evolving field. The insights gained from the literature review, methodology, and results sections contribute to a deeper understanding of the current state of quantum computing and its potential applications.
This chapter discusses a systematic review of the literature available on quantum computers from their theoretical bases through their current advances to their trends in the future. It uses the PRISMA approach to collect such writings from many fields, including physics, computer science, and engineering. It identifies crucial breakthroughs, including Feynman’s conjecture and Shor’s algorithm, and examines how they have affected modern quantum computing paradigms. The said focus areas will center on quantum algorithms, hardware developments in quantum information technology, cryptography, and machine learning, all with an emphasis on their combined contribution to the growth of the field. Identified milestones include achievements of the so-called quantum supremacy and advances made possible by qubit technologies, such as superconducting circuits and ion traps. The review not only presents future challenges, such as scalability, error correction, and noise management, but also pinpoints research gaps and possible avenues for subsequent exploration. The chapter examines the themes of interdisciplinary collaboration and funding trends as well as emerging issues such as quantum cloud computing and hybrid quantum-classical models. Such an overview of the trajectory of quantum computing by this review is also an academic reference as well as a strategic guide for researchers, policymakers, and technologists traversing this fast-evolving field.
Quantum computing, an innovative fusion of quantum mechanics and computer science, has emerged as a transformative force in the field of physics research. This comprehensive review article explores the advancements in quantum computing, focusing on quantum algorithms and their applications in various areas of physics. The review begins with an introduction to the fundamentals of quantum computing, elucidating the principles of qubits, quantum gates, and quantum algorithms. Subsequently, the article delves into the latest developments in quantum algorithms, including Shor's algorithm for factoring large numbers, Grover's algorithm for quantum search, and quantum phase estimation for simulating quantum systems. Furthermore, the review explores the practical applications of quantum computing in physics, encompassing quantum simulations of complex systems, quantum chemistry calculations, and quantum optimization for problem-solving. Additionally, the article presents case studies that demonstrate the practical implications of quantum computing in specific physics applications. The review also addresses the challenges and prospects of quantum computing in physics, including quantum error mitigation, hardware scalability, and quantum-classical interfaces. Ethical and societal considerations related to quantum computing's cryptographic impact, access, and responsible development are also discussed. Furthermore, the review explores the future directions of quantum computing in physics, from quantum supremacy to quantum machine learning and quantum gravity. The article concludes with reflections on the transformative potential of quantum computing in physics research and the importance of collaborative efforts, interdisciplinary research, and responsible development in shaping the future of quantum technologies. Overall, this comprehensive review offers valuable insights into the current state of quantum computing in physics and the exciting possibilities that lie ahead for unravelling the mysteries of the universe.