To overcome the scaling limitations of conventional semiconductor chips, quantum computing has emerged and experienced significant growth in recent years. Quantum computing utilizes resources such as quantum superposition and quantum entanglement to encode and process information. Compared to classical computing, this technology can provide exponential acceleration in the field of ultra-large-scale parallel computing. Consequently, its practical application is anticipated to have profound impacts on information and related technologies. The paper employs a comparative analysis approach to systematically examine the research progress of quantum computer technology. Specifically, the study emphasizes the analysis and consolidation of various quantum computing technology routes, critically evaluates their advantages and disadvantages, and provides a foresight into their future development trends. Currently, research on quantum computing technology is in its early stages and is evolving rapidly. Multiple technical paths are being pursued, resulting in a diverse and competitive landscape that is expected to persist in the short term, as it will take some time before the practical application of quantum computers becomes feasible.
To overcome the scaling limitations of conventional semiconductor chips, quantum computing has emerged and experienced significant growth in recent years. Quantum computing utilizes resources such as quantum superposition and quantum entanglement to encode and process information. Compared to classical computing, this technology can provide exponential acceleration in the field of ultra-large-scale parallel computing. Consequently, its practical application is anticipated to have profound impacts on information and related technologies. The paper employs a comparative analysis approach to systematically examine the research progress of quantum computer technology. Specifically, the study emphasizes the analysis and consolidation of various quantum computing technology routes, critically evaluates their advantages and disadvantages, and provides a foresight into their future development trends. Currently, research on quantum computing technology is in its early stages and is evolving rapidly. Multiple technical paths are being pursued, resulting in a diverse and competitive landscape that is expected to persist in the short term, as it will take some time before the practical application of quantum computers becomes feasible.
Advancements in computer technologies have been evolving in order to provide new services or to improve recent computing performance. Applications of computer technologies to several real-world domains are becoming more realistic and efficient. Two challenges are taken into consideration when applying such technologies including more complicated user requirements and exponential growth of data. In the real world, which is driven by business, achieving user requirements is one promising way of yielding competitive advantages. Moreover, time constraints are also crucial for corporate users. Apart from structured data, unstructured data have been significantly generated via several platforms. Such aspects make data processing more demanding. Quantum technology, which is instantiated in physics, has been utilized in various fields including computer science. Even the real quantum computer is still in its early development, but other concepts such as quantum information and quantum computing are making progress. Furthermore, some quantum-based algorithms have been analytically proven to have higher performance compared to the traditional ones. According to such important milestones, quantum computing has been regarded as one of the key infrastructures of future computing. This paper aims to focus on the main aspects of quantum computing including its backgrounds and recent advancement to provide a clearer picture. Its recent applications to intelligent system enhancement, cybersecurity and cryptography empowerment, and finance are addressed. Several key ideas, and opportunities of quantum computing utilization are also outlined based upon systematic reviews of existing works and case studies. Moreover, comparative analysis between classical and quantum computing in terms of core principles, computational efficiency, and practical feasibility is given. Better understanding and proper preparation of applying quantum computing are thus achieved.
Quantum computation, as part of the broader field of quantum information, represents an assembly of concepts and techniques that concern the nature and processing of information based on quantum mechanics. Quantum computation utilizes unique resources such as quantum superposition and quantum entanglement to encode and process information and has been proved to be dominantly advantageous over classical computation on certain important scientific and engineering problems. Potential applications of quantum computation are expected to influence future information technology and many other related fields deeply and significantly. In this article, we briefly review the history of quantum computation, including how its fundamental ideas and concepts came into being and the development of its significant theories and algorithms. We also discuss the status and outlook of several representative technical routes in this field, including superconducting quantum computation, distributed superconducting quantum computation, photonic quantum computation, trapped-ion quantum computation, silicon-based quantum computation, as well as other systems. Furthermore, by analyzing certain common issues faced by all routes, we propose some thoughts and suggestions for future development of quantum computation in China. We particularly emphasize the following: reinforcement of strategic planning at a national level, establishment of a research team of high caliber, and boost of relevant fundamental research and development of core techniques and critical instruments.
In the article the authors aim at presenting an overview of the current state of quantum computing, exploring qubits, gates, circuits, error correction, sample algorithms, and potential applications as well as an overview of current and near future applications. The article highlights the rapid growth in quantum computing research and argues that now is the opportune time to pursue practical applications. By delving into the fundamental aspects of quantum computing and examining the challenges and advancements in the field, the article provides a comprehensive understanding of the current landscape and emphasizes the importance of scaling and accelerating the development of quantum technologies to unlock their full potential
Quantum computing is an emerging computational paradigm that uses the principles of quantum mechanics, including superposition, entanglement, and quantum interference, to process information in fundamentally different ways from classical computers. During the last decade, quantum computing has progressed from theoretical research toward experimental and cloud-accessible systems. Recent developments have focused on increasing the number and quality of qubits, reducing gate errors, developing quantum error correction, improving quantum software, and integrating quantum processors with classical high-performance computing systems. Despite significant progress, practical large-scale quantum computing remains challenging because quantum states are extremely sensitive to environmental disturbances, resulting in decoherence and computational errors. Other challenges include limited qubit coherence time, gate fidelity, scalability, cryogenic requirements, quantum error correction overhead, hardware connectivity, programming complexity, and the difficulty of demonstrating useful quantum advantage for real-world applications. Recent developments from major research organizations indicate a shift from simply increasing physical qubit counts toward building reliable logical qubits and fault-tolerant quantum systems. Google has reported progress toward error-corrected logical qubits, while IBM\\\'s roadmap focuses on increasingly complex processors, modular architectures, quantum-classical integration, and fault-tolerant systems. Microsoft is pursuing a topological-qubit approach aimed at scalable quantum computing. This paper reviews the current state of quantum computing, examines major technological and scientific challenges, analyzes current research directions, and identifies future opportunities in drug discovery, materials science, optimization, cryptography, artificial intelligence, finance, and scientific simulation. The study concludes that the most realistic future is likely to involve quantum-centric computing, in which quantum processors work together with classical CPUs, GPUs, high-performance computing systems, and quantum networks rather than completely replacing classical computers.
Building on the fundamental principles of quantum computing, this paper sequentially presents the development of quantum computing and its associated application domains. We also analyze and compare the differences between quantum and classical computing, highlighting the benefits of quantum computing for specific problems. To comprehend the advantages of quantum computing in particular fields, extensive research has been conducted in three areas: cryptography, chemistry, and artificial intelligence. We also discuss the wider applications of this emerging technology for future investigation, considering the current state of quantum computing development and anticipated trends.
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.