Quantum Computing: Foundations, Architecture and Applications

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Christopher Columbus Chinnappan, Palani Thanaraj Krishnan, Elakiya Elamaran, Rajakumar Arul, T. Sunil Kumar
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Abstract

Quantum computing exploits the principles of quantum mechanics to address computational problems that are intractable to classical systems. This study examines the evolution, architecture, and applications of the field, with a focus on foundational principles, hardware advancements, and algorithmic progress. Recent quantum processors, such as Google's Willow and IBM's Heron, represent significant advancements in qubit count and gate fidelity; however, they remain constrained by qubit instability, environmental noise, and limitations of current error correction techniques. Quantum algorithms, including Shor's, Grover's, and HHL algorithms, have demonstrated substantial speedups in cryptography, optimization, and machine learning. Nevertheless, the realization of this potential in real-world problems encounters major bottlenecks related to low qubit counts and error correction. Applications span domains such as cryptography, drug discovery, precision medicine, financial modeling, and materials science, in which quantum computation offers potential breakthroughs. However, the development of practical quantum systems presents a substantial challenge. Key programming languages, such as Q#, Qiskit, and Cirq, facilitate algorithmic development and deployment; however, the efficiency of current quantum algorithms is limited by hardware constraints. The future of quantum computing lies in interdisciplinary collaboration, the development of resource-efficient error-correction techniques, and continued hardware development. This study underscores the potential of quantum computing, while emphasizing the research and development required to fully harness its capabilities to address major scientific and technological challenges.

Abstract Image

量子计算:基础、架构和应用
量子计算利用量子力学原理来解决经典系统难以解决的计算问题。本研究考察了该领域的演变、架构和应用,重点是基本原理、硬件进步和算法进步。最近的量子处理器,如谷歌的Willow和IBM的Heron,在量子比特计数和门保真度方面取得了重大进展;然而,它们仍然受到量子比特不稳定性、环境噪声和当前纠错技术的限制。量子算法,包括Shor算法、Grover算法和HHL算法,已经在密码学、优化和机器学习方面证明了显著的加速。然而,在现实问题中实现这种潜力遇到了与低量子位计数和纠错相关的主要瓶颈。应用领域包括密码学、药物发现、精准医疗、金融建模和材料科学,量子计算在这些领域提供了潜在的突破。然而,实际量子系统的发展面临着巨大的挑战。关键的编程语言,如q#、Qiskit和Cirq,促进了算法的开发和部署;然而,当前量子算法的效率受到硬件约束的限制。量子计算的未来在于跨学科合作、资源高效纠错技术的发展以及硬件的持续发展。这项研究强调了量子计算的潜力,同时强调了充分利用其能力应对重大科学和技术挑战所需的研究和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.10
自引率
0.00%
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审稿时长
19 weeks
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