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Microcomputer applications

Research on Quantum Computer and its Applications

HE Xiang-chu, LI Ji-rong

Published Jan 1, 2006• 0 citations
OpenAlex

Abstract

This paper introduces the newest research directions of quantum computation, and expounds the applications of quantum computation technologies in secret communication, cryptography system and database searching. The advantages of quantum computer compared with classical computer and the main factorsthat restrain the current development of quantum computer are also analyzed. Finally, its future development trend is expected.

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This paper introduces the newest research directions of quantum computation, and expounds the applications of quantum computation technologies in secret communication, cryptography system and database searching. The advantages of quantum computer compared with classical computer and the main factorsthat restrain the current development of quantum computer are also analyzed. Finally, its future development trend is expected.
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.
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.
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.
Many countries have invested a large amount of scientific research funds into supporting quantum information technology and proposed many policies to support the three main quantum technology fields: quantum sensing, quantum communication and quantum computing. Many science and technology giants have also provided quantum cloud computing experimental platforms that can provide quantum access online. With the investment of various technologies and resources, quantum information technology has developed rapidly. The combination of quantum computing and neural networks is a research branch that has attracted much attention in the field of quantum computing in recent years. It mainly involves the study of how to exploit the computational acceleration advantage of quantum computing to deal with various problems solved by neural networks in traditional artificial intelligence. In this paper, the recent development of the quantum computer is widely investigated, and a quantum neural network is briefly analyzed. Finally, the performance of the quantum neural network and quantum optimization is discussed, and future research directions are proposed.