Reversible quantum communication & systems

IF 2.5 Q3 QUANTUM SCIENCE & TECHNOLOGY IET Quantum Communication Pub Date : 2022-03-15 DOI:10.1049/qtc2.12037
Diganta Sengupta, Ahmed Abd El-Latif, Debashis De, Keivan Navi, Nader Bagherzadeh
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引用次数: 1

Abstract

Quantum Computing has emerged as one of the important dimensions of global research lately, on both the prospects, hardware as well as algorithms. With enhanced processing powers, several architectures based on adiabatic concepts resulting in reversibility have been proposed to date. Architectures based on Quantum Dot Cellular Automata have also shown considerable promise for realising the concept of reversibility. Recently, research has been focussed on the application of quantum computing for faster and secure communication. Dedicated machine learning algorithms and neural networks for quantum computation have also attracted considerable research. With a plethora of research and advances in this domain, this Special Issue publishes outstanding contributions for dissemination of the knowledge of Reversible Quantum Communication & Systems. This Special Issue publishes latest approaches and findings in Quantum Algorithms and Reversible Computing with focus on emerging Machine Learning approaches in Quantum Communications. Reversible Logic forms a pivotal part of Quantum Computing and has been a topic of high interest among Quantum Computing Scientists and researchers throughout the last decade. It also exhibits considerable prospects in recent research due to its adiabatic characteristics. Logic synthesis and optimisation algorithms within the purview of Reversibility have witnessed credible approaches and pose future prospects, such as the rise of Machine Learning approaches which have also penetrated the Quantum Domain.

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可逆量子通信与系统
近年来,量子计算已成为全球研究的重要领域之一,无论是在前景、硬件还是算法方面。随着处理能力的增强,迄今为止已经提出了几种基于绝热概念的体系结构,从而导致可逆性。基于量子点元胞自动机的架构在实现可逆性概念方面也显示出相当大的希望。近年来,研究重点是应用量子计算实现更快、更安全的通信。用于量子计算的专用机器学习算法和神经网络也吸引了大量的研究。随着这一领域的大量研究和进展,本期特刊发表了对可逆量子通信知识传播的杰出贡献。系统。这一期特刊发表了量子算法和可逆计算的最新方法和发现,重点是量子通信中新兴的机器学习方法。可逆逻辑是量子计算的关键组成部分,在过去十年中一直是量子计算科学家和研究人员高度感兴趣的话题。由于它的绝热特性,在最近的研究中也显示出相当大的前景。可逆性范围内的逻辑综合和优化算法已经见证了可靠的方法,并提出了未来的前景,例如机器学习方法的兴起也渗透到了量子领域。
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CiteScore
6.70
自引率
0.00%
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0
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