Temporal Pattern Recognition with Delayed-Feedback Spin-Torque Nano-Oscillators

Riou, M.; Torrejon, J.; Garitaine, B.; Araujo, F. Abreu; Bortolotti, P.; Cros, V.; Tsunegi, S.; Yakushiji, K.; Fukushima, A.; Kubota, H.; Yuasa, S.; Querlioz, D.; Stiles, M. D.; Grollier, Julie

doi:10.1103/physrevapplied.12.024049

Title: Temporal Pattern Recognition with Delayed-Feedback Spin-Torque Nano-Oscillators

Journal Article · Fri Aug 23 00:00:00 EDT 2019 · Physical Review Applied

DOI:https://doi.org/10.1103/physrevapplied.12.024049· OSTI ID:1613161

Riou, M. ^[1]; Torrejon, J. ^[1]; Garitaine, B. ^[1]; Araujo, F. Abreu ^[1]; Bortolotti, P. ^[1]; Cros, V. ^[1]; Tsunegi, S. ^[2]; Yakushiji, K. ^[2]; Fukushima, A. ^[2]; Kubota, H. ^[2]; Yuasa, S. ^[2]; Querlioz, D. ^[3]; Stiles, M. D. ^[4]; Grollier, Julie ^[1]

Univ. Paris-Saclay, Palaiseau (France)
National Inst. of Advanced Industrial Science and Technology (AIST), Ibaraki (Japan)
Univ. Paris-Saclay, Orsay (France)
National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States)

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. We extend the memory of the spin-torque nano-oscillators through time-delayed feedback. We leverage this extrinsic memory to increase the efficiency of solving pattern recognition tasks that require memory to discriminate different inputs. Here, the large tunability of these nonlinear oscillators allows us to control and optimize the delayed-feedback memory using different operating conditions of applied current and magnetic field.

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Research Organization:: Energy Frontier Research Centers (EFRC) (United States). Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C); Univ. of California, San Diego, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: SC0019273

OSTI ID:: 1613161

Alternate ID(s):: OSTI ID: 1564596

Journal Information:: Physical Review Applied, Vol. 12, Issue 2; ISSN 2331-7019

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 29 works

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Machine learning based on reservoir computing with time-delayed optoelectronic and photonic systems Chembo, Yanne K. Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 30, Issue 1 https://doi.org/10.1063/1.5120788	journal	January 2020

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Title: Temporal Pattern Recognition with Delayed-Feedback Spin-Torque Nano-Oscillators

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