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31 results on '"Namiki, Wataru"'

2. A Redox-based Ion-Gating Reservoir, Utilizing Double Reservoir States in Drain and Gate Nonlinear Responses

Author

Wada, Tomoki, Nishioka, Daiki, Namiki, Wataru, Tsuchiya, Takashi, Higuchi, Tohru, and Terabe, Kazuya

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

We have demonstrated physical reservoir computing with a redox-based ion-gating reservoir (redox-IGR) comprising LixWO3 thin film and lithium ion conducting glass ceramic (LICGC). The subject redox-IGR successfully solved a second-order nonlinear dynamic equation by utilizing voltage pulse driven ion-gating in a LixWO3 channel to enable reservoir computing. Under the normal conditions, in which only the drain current (ID) is used for the reservoir states, the lowest prediction error is 7.39x10-4. Performance was enhanced by the addition of IG to the reservoir states, resulting in a significant lowering of the prediction error to 5.06x10-4, which is noticeably lower than other types of physical reservoirs reported to date. A second-order nonlinear autoregressive moving average (NARMA2) task, a typical benchmark of reservoir computing, was also performed with the IGR and good performance was achieved, with an NMSE of 0.163. A short-term memory task was performed to investigate an enhancement mechanism resulting from the IG addition. An increase in memory capacity, from 1.87 without IG to 2.73 with IG, was observed in the forgetting curves, indicating that enhancement of both high dimensionality and memory capacity are attributed to the origin of the performance improvement., Comment: 22 pages, 4 figures

Published
2022

3. Experimental Demonstration of High-Performance Physical Reservoir Computing with Nonlinear Interfered Spin Wave Multi-Detection

Author

Namiki, Wataru, Nishioka, Daiki, Yamaguchi, Yu, Tsuchiya, Takashi, Higuchi, Tohru, and Terabe, Kazuya

Subjects
Computer Science - Emerging Technologies, Physics - Applied Physics
Abstract

Physical reservoir computing, which is a promising method for the implementation of highly efficient artificial intelligence devices, requires a physical system with nonlinearity, fading memory, and the ability to map in high dimensions. Although it is expected that spin wave interference can perform as highly efficient reservoir computing in some micromagnetic simulations, there has been no experimental verification to date. Herein, we demonstrate reservoir computing that utilizes multidetected nonlinear spin wave interference in an yttrium iron garnet single crystal. The subject computing system achieved excellent performance when used for hand-written digit recognition, second-order nonlinear dynamical tasks, and nonlinear autoregressive moving average (NARMA). It is of particular note that normalized mean square errors (NMSEs) for NARMA2 and second-order nonlinear dynamical tasks were 1.81x10-2 and 8.37x10-5, respectively, which are the lowest figures for any experimental physical reservoir so far reported. Said high performance was achieved with higher nonlinearity and the large memory capacity of interfered spin wave multi-detection., Comment: 19 pages, 5 figures

Published
2022

4. Edge-Of-Chaos Learning Achieved by Ion-Electron Coupled Dynamics in an Ion-Gating Reservoir

Author

Nishioka, Daiki, Tsuchiya, Takashi, Namiki, Wataru, Takayanagi, Makoto, Imura, Masataka, Koide, Yasuo, Higuchi, Tohru, and Terabe, Kazuya

Subjects
Computer Science - Emerging Technologies, Physics - Applied Physics
Abstract

Physical reservoir computing has recently been attracting attention for its ability to significantly reduce the computational resources required to process time-series data. However, the physical reservoirs that have been reported to date have had insufficient expression power, and most of them have a large volume, which makes their practical application difficult. Herein we describe the development of a Li+-electrolyte based ion-gating reservoir (IGR), with ion-electron coupled dynamics, for use in high performance physical reservoir computing. A variety of synaptic responses were obtained in response to past experience, which responses were stored as transient charge density patterns in an electric double layer, at the Li+-electrolyte/diamond interface. Performance, which was tested using a nonlinear autoregressive moving-average (NARMA) task, was found to be excellent, with a NMSE of 0.023 for NARMA2, which is the highest for any physical reservoir reported to date. The maximum Lyapunov exponent of the IGR was 0.0083: the edge of chaos state enabling the best computational capacity. The IGR described herein opens the way for high-performance and integrated neural network devices., Comment: 25 pages, 5 figures for main part and 4 figures for Supplementary information

Published
2022

14. Asymmetric transition of electrical resistance in an all-solid-state redox device with Fe3O4and Li-ion electrolyte thin films for physical reservoir computing

Author

Namiki, Wataru, Tsuchiya, Takashi, Nishioka, Daiki, Higuchi, Tohru, and Terabe, Kazuya

Abstract

In recent years, ion-gating devices have been used in artificial neuromorphic computing and achieved high performance for time-series data processing. However, the origin of this performance still needs to be clarified. In this study, we fabricated an all-solid-state redox device with functional material Fe3O4and Li-ion conducting solid electrolytes, and the transient response of the electrical resistance of the Fe3O4thin film to time-series data input was investigated. The transition between high and low electrical resistance states was asymmetric, and residual Li-ion in the thin film led to a hysteresis effect. These unique features, which are induced by ion-electron dynamics coupling, contributes to the high performance of physical reservoir computing utilizing an ion-gating device.

Published
2024
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17. Inverted input method for computing performance enhancement of the ion-gating reservoir

Author

Yamaguchi, Yu, Nishioka, Daiki, Namiki, Wataru, Tsuchiya, Takashi, Imura, Masataka, Koide, Yasuo, Higuchi, Tohru, and Terabe, Kazuya

Abstract

Physical reservoir computing (PRC) is useful for edge computing, although the challenge is to improve computational performance. In this study, we developed an inverted input method, the inverted input is additionally applied to a physical reservoir together with the original input, to improve the performance of the ion-gating reservoir. The error in the second-order nonlinear equation task was 7.3 × 10−5, the lowest error in reported PRC to date. Improvement of high dimensionality by the method was confirmed to be the origin of the performance enhancement. This inverted input method is versatile enough to enhance the performance of any other PRC.

Published
2024
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29. Hole-Proton Mixed Conduction of Perovskite-Oxide Thin Film with Oxygen Vacancies and Lattice Distortion for SOFC Electrode

Author

Higuchi, Tohru, Furuichi, Shoto, Namiki, Wataru, Takayanagi, Makoto, Minohara, Makoto, Horiba, Koji, Kumigashira, Hiroshi, and Tsuchiya, Takashi

Abstract

Y3+-doped BaPrO3 (BaPr0.8Y0.2O3-d: BPYO) thin film was prepared on Al2O3 (0006) substrate by RF magnetron sputtering. The as-deposited BPYO thin film prepared at 600oC exhibits the a- an c-axes orientation. The electrical conductivity slightly increases in the wet atmosphere and does not much depend on the oxygen partial pressure at 300~600degC. The hole and proton-induced levels are observed at the top of valence band and near the Fermi level, respectively. These results indicate that the BPYO thin film has the hole-proton mixed conduction, which is required for anode of solid state oxide fuel cells.

Published
2017

30. Electron-Ion Mixed Conduction of Nd0.6Sr0.4FeO3 Cathode Electrode Thin Film for Solid Oxide Fuel Cell

Author

Namiki, Wataru, Takayanagi, Makoto, Furuichi, Shoto, Tsuchiya, Takashi, Minohara, Makoto, Kobayashi, Masaki, Horiba, Koji, Kumigashira, Hiroshi, and Higuchi, Tohru

Abstract

Nd0.6Sr0.4FeO3 (NSFO) thin films with various thicknesses have been deposited on Al2O3 (0001) substrates by RF magnetron sputtering. The lattice constant decreases with increasing film thickness. The electrical conductivity is higher than that of the bulk crystal. The conductivity at 500@C does not depend on the oxygen gas partial pressure. The value of band gap corresponds to the activation energy calculated from Arrhenius plots. These results indicate that NSFO thin film has the high electron conduction in addition to oxygen-ion conduction at 500@C.

Published
2017

31. Unexpected metal-insulator transition in thick Ca1-<italic>x</italic>Sr<italic>x</italic>VO3 film on SrTiO3 (100) single crystal.

Author

Higuchi, Tohru, Takayanagi, Makoto, Namiki, Wataru, Tsuchiya, Takashi, Terabe, Kazuya, Ueda, Shigenori, Minohara, Makoto, Horiba, Koji, and Kumigashira, Hiroshi

Subjects
METAL-insulator transitions, EPITAXIAL layers, X-ray photoelectron spectroscopy, MAGNETORESISTANCE, ELECTRON-electron interactions
Abstract

Epitaxial Ca1-xSrxVO3 (0 ≦ x ≦ 1) thin films were grown on (100)-oriented SrTiO3 substrates by using the pulsed laser deposition technique. In contrast to the previous report that metal-insulator transition (MIT) in Ca1-xSrxVO3 (CSVO) was achieved only for extremely thin films (several nm thick), MIT was observed at 39, 72, and 113 K for films with a thickness of 50 nm. The electronic structure was investigated by hard and soft X-ray photoemission spectroscopy (HX-PES and SX-PES). The difference between these PES results was significant due to the variation in an escape depth of photoelectrons of PES. While HX-PES showed that the V 2p3/2 spectra consisted of four peaks (V5+, V4+, V3+, and V2+/1+), SX-PES showed only three peaks (V5+, V4+, and V3+). This difference can be caused by a strain from the substrate, which leads to the chemical disorder (V5+, V4+, V3+, and V2+/1+). The thin film near the substrate is affected by the strain. The positive magnetoresistance is attributed to the effect of electron-electron interactions in the disorder system. Therefore, the emergence of MIT can be explained by the electron-electron interactions from the chemical disorder due to the strain. [ABSTRACT FROM AUTHOR]

Published
2018
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