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arXiv quant-ph/9802028quant-phcs.CV
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用于数据分析的量子计算机

Analogue Quantum Computers for Data Analysis

Alexander Yu. Vlasov

摘要:

模拟计算机使用物理系统的连续属性进行建模。本文介绍了用模拟量子计算机对某些数据分析模型进行建模的可能性。它是一种模拟联想记忆和形式神经网络。该模型的一个特殊性是连续的内部过程与离散的输出状态集的组合。很久以前就有人用经典的模拟计算机对系统进行建模,但现在与现代数字计算机相比,它不是很有效。量子模拟模型的应用在现代技术水平上看起来是完全可能的,并且可能比数字模型更有效,因为元素的数量可能是大约Avogadro数(N=6.0E23)。

英文摘要:

Analogue computers use continuous properties of physical system for modeling. In the paper is described possibility of modeling by analogue quantum computers for some model of data analysis. It is analogue associative memory and a formal neural network. A particularity of the models is combination of continuous internal processes with discrete set of output states. The modeling of the system by classical analogue computers was offered long times ago, but now it is not very effectively in comparison with modern digital computers. The application of quantum analogue modelling looks quite possible for modern level of technology and it may be more effective than digital one, because number of element may be about Avogadro number (N=6.0E23).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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