NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Neuromorphic computing with nanoscale spintronic oscillators
Published
Author(s)
Jacob Torrejon, Mathieu Riou, Flavio Abreu Araujo, Sumito Tsunegi, Guru Khalsa, Damien Querlioz, Paolo Bortolotti, Vincent Cros, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Mark D. Stiles, Julie Grollier
Abstract
In the brain, hundred billions of neurons develop rhythmic activities and interact to process information. Taking inspiration from this behavior to realize high density, low power neuromorphic computing requires coupling huge numbers of nanoscale non-linear oscillators. However, there is no proof of concept today of neuromorphic computing with nanoscale oscillators. Indeed, nanodevices tend to be noisy and to lack the stability required to process data in a reliable way. Here, we show experimentally that, thanks to its well-controlled magnetization dynamics, a single nanoscale magnetic oscillator can recognize spoken digits at the state of the art compared to existing neural networks. We pinpoint the properties of the dynamical regime leading to highest performance in the bias conditions space. This result, combined with the exceptional ability of these magnetic oscillators to interact with other oscillators, their long lifetime, and low energy consumption, opens the path to fast parallel on-chip computations based on coupled networks of oscillators.
Torrejon, J.
, Riou, M.
, Abreu Araujo, F.
, Tsunegi, S.
, Khalsa, G.
, Querlioz, D.
, Bortolotti, P.
, Cros, V.
, Yakushiji, K.
, Fukushima, A.
, Kubota, H.
, Yuasa, S.
, Stiles, M.
and Grollier, J.
(2017),
Neuromorphic computing with nanoscale spintronic oscillators, Nature, [online], https://doi.org/10.1038/nature23011, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=922599
(Accessed October 4, 2025)