Abstract Advances in quantum technologies have prompted renewed interest in computational models that extend beyond the capabilities of classical systems. Quantum computing, grounded in the principles of quantum mechanics, introduces novel mechanisms for information processing that challenge conventional assumptions in computer science. This paper critically examines the role of quantum computing across core computer science domains by integrating foundational theory with application-oriented research. Existing studies in cryptography, optimization, artificial intelligence, database search, and system simulation are analyzed to assess both demonstrated capabilities and practical constraints. The discussion emphasizes the increasing relevance of hybrid quantum–classical approaches in the current technological landscape, while identifying key limitations related to scalability, noise, and algorithmic feasibility. By consolidating theoretical insights with applied perspectives, this work provides a realistic assessment of the present state of quantum computing and outlines research directions essential for its effective integration into future computational systems.
Abstract Advances in quantum technologies have prompted renewed interest in computational models that extend beyond the capabilities of classical systems. Quantum computing, grounded in the principles of quantum mechanics, introduces novel mechanisms for information processing that challenge conventional assumptions in computer science. This paper critically examines the role of quantum computing across core computer science domains by integrating foundational theory with application-oriented research. Existing studies in cryptography, optimization, artificial intelligence, database search, and system simulation are analyzed to assess both demonstrated capabilities and practical constraints. The discussion emphasizes the increasing relevance of hybrid quantum–classical approaches in the current technological landscape, while identifying key limitations related to scalability, noise, and algorithmic feasibility. By consolidating theoretical insights with applied perspectives, this work provides a realistic assessment of the present state of quantum computing and outlines research directions essential for its effective integration into future computational systems.
Abstract Advances in quantum technologies have prompted renewed interest in computational models that extend beyond the capabilities of classical systems. Quantum computing, grounded in the principles of quantum mechanics, introduces novel mechanisms for information processing that challenge conventional assumptions in computer science. This paper critically examines the role of quantum computing across core computer science domains by integrating foundational theory with application-oriented research. Existing studies in cryptography, optimization, artificial intelligence, database search, and system simulation are analyzed to assess both demonstrated capabilities and practical constraints. The discussion emphasizes the increasing relevance of hybrid quantum–classical approaches in the current technological landscape, while identifying key limitations related to scalability, noise, and algorithmic feasibility. By consolidating theoretical insights with applied perspectives, this work provides a realistic assessment of the present state of quantum computing and outlines research directions essential for its effective integration into future computational systems.
ABSTRACT Quantum computing represents a fundamental shift in the way computational problems are approached and solved. Unlike classical computing systems that rely on binary bits to process information, quantum computing utilizes quantum bits, or qubits, which exploit principles of quantum mechanics such as superposition and entanglement. This transition from classical bits to qubits has opened new possibilities for solving complex problems that are computationally infeasible for traditional systems. This paper explores the evolution of computing paradigms from classical architectures to quantum-based models, highlighting the theoretical foundations and technological advancements that have driven this transformation. It discusses the core concepts of quantum computing, including qubit representation, quantum gates, and computational models, along with an overview of current quantum hardware architectures. Furthermore, the paper examines key application areas such as cryptography, optimization, artificial intelligence, and scientific simulations, where quantum computing demonstrates significant potential. Despite its promise, quantum computing faces substantial challenges related to hardware stability, error correction, scalability, and resource requirements, which are also analyzed. Finally, the paper outlines future research directions and the potential impact of quantum computing on next-generation information processing systems, emphasizing its role in redefining the boundaries of modern computation. Keywords : Quantum Computing, Qubits, Quantum Algorithms, Quantum Applications, Future Computing Technologies
Quantum computing grounded in principles of superposition, entanglement, and quantum interference, represents a paradigm shift in computation, surpassing the capabilities of classical systems for specific domains. This paper reviews the historical foundations, theoretical principles, hardware architectures, and software ecosystems of quantum computing. It highlights transformative applications across cryptography, artificial intelligence, finance, healthcare, and climate science, while addressing critical challenges such as decoherence, scalability, and algorithmic limitations. Finally, it outlines future directions including fault-tolerant processors, hybrid quantum-classical architectures, and global policy frameworks. The study consolidates research to provide a holistic perspective on the trajectory of quantum technologies in the 21st century.
Quantum computing is an advanced computational paradigm that leverages principles of quantum mechanics, including superposition, entanglement, and interference, to process information more efficiently than classical systems [1][2]. Unlike classical bits, qubits can exist in multiple states simultaneously, enabling exponential computational capabilities for complex problem-solving. Since its theoretical foundations proposed by Richard Feynman and further developed by David Deutsch, quantum computing has progressed into an active research and industrial domain [2][3]. This paper presents an overview of the core concepts of quantum computation, technological evolution, and key algorithms such as Shor’s and Grover’s, which demonstrate significant computational advantages [9][10]. It also explores major application areas including cryptography, healthcare, artificial intelligence, and optimization, while addressing critical challenges such as decoherence, error correction, and scalability [5][6]. The study highlights future prospects, emphasizing the potential of quantum computing to transform scientific and industrial domains [12][15].
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 represents a transformative shift in computational technology, leveraging the principles of quantum mechanics to process information in ways that surpass the limits of classical systems.By exploiting qubits, superposition, entanglement, and quantum parallelism, quantum computers offer the potential to solve certain classes of problems-such as optimization, cryptography, molecular simulation, and complex machine learning tasks-significantly faster than classical algorithms.With rapid advancements in quantum hardware and the emergence of Noisy Intermediate-Scale Quantum (NISQ) devices, quantum computing has evolved from a theoretical concept to a practical field with growing industrial and scientific relevance.Although current systems face challenges related to error rates, decoherence, and scalability, ongoing developments in quantum error correction, hybrid quantum-classical algorithms, and software frameworks like Qiskit, Cirq, and PennyLane continue to push the field forward.This paper provides an introductory overview of quantum computing, outlining its foundational principles, current technological landscape, key algorithms, and future research directions.The goal is to offer a clear understanding of how quantum computing is poised to reshape the future of computation.