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p-bits for probabilistic spin logic

delete2019-03-11
delete133
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OA
AI
K
Kerem Y. Çamsarı *
B
Brian Sutton
D
Datta, Supriyo
DOI:10.1063/1.5055860delete
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摘要

摘要

En 中文
We introduce the concept of a probabilistic or p-bit, intermediate between the standard bits of digital electronics and the emerging q-bits of quantum computing. We show that low barrier magnets or LBMs provide a natural physical representation for p-bits and can be built either from perpendicular magnets designed to be close to the in-plane transition or from circular in-plane magnets. Magnetic tunnel junctions (MTJs) built using LBMs as free layers can be combined with standard NMOS transistors to provide three-terminal building blocks for large scale probabilistic circuits that can be designed to perform useful functions. Interestingly, this three-terminal unit looks just like the 1T/MTJ device used in embedded magnetic random access memory technology, with only one difference: the use of an LBM for the MTJ free layer. We hope that the concept of p-bits and p-circuits will help open up new application spaces for this emerging technology. However, a p-bit need not involve an MTJ; any fluctuating resistor could be combined with a transistor to implement it, while completely digital implementations using conventional CMOS technology are also possible. The p-bit also provides a conceptual bridge between two active but disjoint fields of research, namely, stochastic machine learning and quantum computing. First, there are the applications that are based on the similarity of a p-bit to the binary stochastic neuron (BSN), a well-known concept in machine learning. Three-terminal p-bits could provide an efficient hardware accelerator for the BSN. Second, there are the applications that are based on the p-bit being like a poor man's q-bit. Initial demonstrations based on full SPICE simulations show that several optimization problems, including quantum annealing are amenable to p-bit implementations which can be scaled up at room temperature using existing technology. Published under license by AIP Publishing.
Keyword:
MEMORY
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期刊

Applied Physics Reviews 封面图
Applied Physics Reviews
IF:
11.6
论文数:
1.2K
被引数:
1.3W

机构

Purdue University System 封面图
Purdue University System
学者数:
4.0W
论文数: 3.6W
被引数: 66
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