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Step-like dependence of memory function on pulse width in spintronics reservoir computing
Physical reservoir computing is a type of recurrent neural network that applies the dynamical response from physical systems to information processing. However, the relation between computation performance and physical parameters/phenomena still remains unclear. This study reports our progress regar...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659325/ https://www.ncbi.nlm.nih.gov/pubmed/33177539 http://dx.doi.org/10.1038/s41598-020-76142-x |
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author | Yamaguchi, Terufumi Akashi, Nozomi Nakajima, Kohei Kubota, Hitoshi Tsunegi, Sumito Taniguchi, Tomohiro |
author_facet | Yamaguchi, Terufumi Akashi, Nozomi Nakajima, Kohei Kubota, Hitoshi Tsunegi, Sumito Taniguchi, Tomohiro |
author_sort | Yamaguchi, Terufumi |
collection | PubMed |
description | Physical reservoir computing is a type of recurrent neural network that applies the dynamical response from physical systems to information processing. However, the relation between computation performance and physical parameters/phenomena still remains unclear. This study reports our progress regarding the role of current-dependent magnetic damping in the computational performance of reservoir computing. The current-dependent relaxation dynamics of a magnetic vortex core results in an asymmetric memory function with respect to binary inputs. A fast relaxation caused by a large input leads to a fast fading of the input memory, whereas a slow relaxation by a small input enables the reservoir to keep the input memory for a relatively long time. As a result, a step-like dependence is found for the short-term memory and parity-check capacities on the pulse width of input data, where the capacities remain at 1.5 for a certain range of the pulse width, and drop to 1.0 for a long pulse-width limit. Both analytical and numerical analyses clarify that the step-like behavior can be attributed to the current-dependent relaxation time of the vortex core to a limit-cycle state. |
format | Online Article Text |
id | pubmed-7659325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76593252020-11-13 Step-like dependence of memory function on pulse width in spintronics reservoir computing Yamaguchi, Terufumi Akashi, Nozomi Nakajima, Kohei Kubota, Hitoshi Tsunegi, Sumito Taniguchi, Tomohiro Sci Rep Article Physical reservoir computing is a type of recurrent neural network that applies the dynamical response from physical systems to information processing. However, the relation between computation performance and physical parameters/phenomena still remains unclear. This study reports our progress regarding the role of current-dependent magnetic damping in the computational performance of reservoir computing. The current-dependent relaxation dynamics of a magnetic vortex core results in an asymmetric memory function with respect to binary inputs. A fast relaxation caused by a large input leads to a fast fading of the input memory, whereas a slow relaxation by a small input enables the reservoir to keep the input memory for a relatively long time. As a result, a step-like dependence is found for the short-term memory and parity-check capacities on the pulse width of input data, where the capacities remain at 1.5 for a certain range of the pulse width, and drop to 1.0 for a long pulse-width limit. Both analytical and numerical analyses clarify that the step-like behavior can be attributed to the current-dependent relaxation time of the vortex core to a limit-cycle state. Nature Publishing Group UK 2020-11-11 /pmc/articles/PMC7659325/ /pubmed/33177539 http://dx.doi.org/10.1038/s41598-020-76142-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yamaguchi, Terufumi Akashi, Nozomi Nakajima, Kohei Kubota, Hitoshi Tsunegi, Sumito Taniguchi, Tomohiro Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title | Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title_full | Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title_fullStr | Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title_full_unstemmed | Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title_short | Step-like dependence of memory function on pulse width in spintronics reservoir computing |
title_sort | step-like dependence of memory function on pulse width in spintronics reservoir computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659325/ https://www.ncbi.nlm.nih.gov/pubmed/33177539 http://dx.doi.org/10.1038/s41598-020-76142-x |
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