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Title: Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting

Abstract

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [1]; ORCiD logo [1]
  1. Imperial College, London (United Kingdom)
  2. Imperial College, London (United Kingdom); Kyushu Univ., Fukuoka (Japan)
  3. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
2282531
Report Number(s):
LA-UR-21-29487
Journal ID: ISSN 1748-3387
Grant/Contract Number:  
89233218CNA000001; AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Nature Nanotechnology
Additional Journal Information:
Journal Volume: 17; Journal Issue: 5; Journal ID: ISSN 1748-3387
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; computer science; spin ice; reservoir computing; vortex spin ice; electrical and electronic engineering; energy efficiency; magnetic devices; magnetic properties and materials; metamaterials

Citation Formats

Gartside, Jack Carter, Stenning, Kilian D., Vanstone, Alex, Holder, Holly H., Arroo, Daan M., Dion, Troy, Caravelli, Francesco, Kurebayashi, Hidekazu, and Branford, Will R. Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting. United States: N. p., 2022. Web. doi:10.1038/s41565-022-01091-7.
Gartside, Jack Carter, Stenning, Kilian D., Vanstone, Alex, Holder, Holly H., Arroo, Daan M., Dion, Troy, Caravelli, Francesco, Kurebayashi, Hidekazu, & Branford, Will R. Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting. United States. https://doi.org/10.1038/s41565-022-01091-7
Gartside, Jack Carter, Stenning, Kilian D., Vanstone, Alex, Holder, Holly H., Arroo, Daan M., Dion, Troy, Caravelli, Francesco, Kurebayashi, Hidekazu, and Branford, Will R. Thu . "Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting". United States. https://doi.org/10.1038/s41565-022-01091-7. https://www.osti.gov/servlets/purl/2282531.
@article{osti_2282531,
title = {Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting},
author = {Gartside, Jack Carter and Stenning, Kilian D. and Vanstone, Alex and Holder, Holly H. and Arroo, Daan M. and Dion, Troy and Caravelli, Francesco and Kurebayashi, Hidekazu and Branford, Will R.},
abstractNote = {Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.},
doi = {10.1038/s41565-022-01091-7},
journal = {Nature Nanotechnology},
number = 5,
volume = 17,
place = {United States},
year = {Thu May 05 00:00:00 EDT 2022},
month = {Thu May 05 00:00:00 EDT 2022}
}

Works referenced in this record:

Neuromorphic computing with nanoscale spintronic oscillators
journal, July 2017

  • Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu
  • Nature, Vol. 547, Issue 7664
  • DOI: 10.1038/nature23011

Dynamically Driven Emergence in a Nanomagnetic System
journal, February 2021

  • Dawidek, Richard W.; Hayward, Thomas J.; Vidamour, Ian T.
  • Advanced Functional Materials, Vol. 31, Issue 15
  • DOI: 10.1002/adfm.202008389

Magnonic Bending, Phase Shifting and Interferometry in a 2D Reconfigurable Nanodisk Crystal
journal, December 2020


Current-controlled nanomagnetic writing for reconfigurable magnonic crystals
journal, November 2020


The design and verification of MuMax3
journal, October 2014

  • Vansteenkiste, Arne; Leliaert, Jonathan; Dvornik, Mykola
  • AIP Advances, Vol. 4, Issue 10
  • DOI: 10.1063/1.4899186

Thermal ground-state ordering and elementary excitations in artificial magnetic square ice
journal, November 2010

  • Morgan, Jason P.; Stein, Aaron; Langridge, Sean
  • Nature Physics, Vol. 7, Issue 1
  • DOI: 10.1038/nphys1853

Anisotropic MagnetoMemristance
journal, June 2022


Magnetic texture based magnonics
journal, April 2021


Nanoscale neural network using non-linear spin-wave interference
journal, November 2021


Advances in artificial spin ice
journal, November 2019

  • Skjærvø, Sandra H.; Marrows, Christopher H.; Stamps, Robert L.
  • Nature Reviews Physics, Vol. 2, Issue 1
  • DOI: 10.1038/s42254-019-0118-3

Domain wall trajectory determined by its fractional topological edge defects
journal, July 2013

  • Pushp, Aakash; Phung, Timothy; Rettner, Charles
  • Nature Physics, Vol. 9, Issue 8
  • DOI: 10.1038/nphys2669

Thermoplasmonic Nanomagnetic Logic Gates
journal, August 2022


Ground State Lost but Degeneracy Found: The Effective Thermodynamics of Artificial Spin Ice
journal, May 2007


Computation in artificial spin ice
conference, January 2018

  • Jensen, Johannes H.; Folven, Erik; Tufte, Gunnar
  • The 2018 Conference on Artificial Life
  • DOI: 10.1162/isal_a_00011

Stability of magnetic vortex in soft magnetic nano-sized circular cylinder
journal, April 2002


Field-induced phase coexistence in an artificial spin ice
journal, December 2018


A tunable magnetic metamaterial based on the dipolar four-state Potts model
journal, October 2018


Reservoir computing using dynamic memristors for temporal information processing
journal, December 2017


Emergent Spin Dynamics Enabled by Lattice Interactions in a Bicomponent Artificial Spin Ice
journal, February 2021


Physics for neuromorphic computing
journal, July 2020

  • Marković, Danijela; Mizrahi, Alice; Querlioz, Damien
  • Nature Reviews Physics, Vol. 2, Issue 9
  • DOI: 10.1038/s42254-020-0208-2

Reconfigurable magnonic mode-hybridisation and spectral control in a bicomponent artificial spin ice
journal, May 2021


Magnetic Tunability of Permalloy Artificial Spin Ice Structures
journal, January 2020


Direct observation of the vortex core magnetization and its dynamics
journal, May 2007

  • Chou, K. W.; Puzic, A.; Stoll, H.
  • Applied Physics Letters, Vol. 90, Issue 20
  • DOI: 10.1063/1.2738186

Reservoir Computing With Spin Waves Excited in a Garnet Film
journal, January 2018


Reconfigurable magnonics heats up
journal, June 2015


Magnetic Vortex Core Observation in Circular Dots of Permalloy
journal, August 2000


Tunable magnetization dynamics in artificial spin ice via shape anisotropy modification
journal, August 2019


MuMax: A new high-performance micromagnetic simulation tool
journal, November 2011

  • Vansteenkiste, A.; Van de Wiele, B.
  • Journal of Magnetism and Magnetic Materials, Vol. 323, Issue 21
  • DOI: 10.1016/j.jmmm.2011.05.037

Dynamic response of an artificial square spin ice
journal, March 2016


Reservoir Computing in Artificial Spin Ice
conference, January 2020

  • Jensen, Johannes H.; Tufte, Gunnar
  • The 2020 Conference on Artificial Life
  • DOI: 10.1162/isal_a_00268

Magnonic crystals for data processing
journal, May 2017

  • Chumak, A. V.; Serga, A. A.; Hillebrands, B.
  • Journal of Physics D: Applied Physics, Vol. 50, Issue 24
  • DOI: 10.1088/1361-6463/aa6a65

Recent advances in physical reservoir computing: A review
journal, July 2019


Direct observation of magnetic monopole defects in an artificial spin-ice system
journal, April 2010

  • Ladak, S.; Read, D. E.; Perkins, G. K.
  • Nature Physics, Vol. 6, Issue 5
  • DOI: 10.1038/nphys1628

Numerical simulation of artificial spin ice for reservoir computing
journal, January 2021


In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks
journal, October 2021


A novel method for the injection and manipulation of magnetic charge states in nanostructures
journal, September 2016

  • Gartside, J. C.; Burn, D. M.; Cohen, L. F.
  • Scientific Reports, Vol. 6, Issue 1
  • DOI: 10.1038/srep32864

Memory formation in matter
journal, July 2019


Reservoir computing approaches to recurrent neural network training
journal, August 2009


Advances in Magnetics Roadmap on Spin-Wave Computing
journal, June 2022


Magnon Modes of Microstates and Microwave-Induced Avalanche in Kagome Artificial Spin Ice with Topological Defects
journal, September 2020


Artificial spin ice phase-change memory resistors
journal, February 2022

  • Caravelli, Francesco; Chern, Gia-Wei; Nisoli, Cristiano
  • New Journal of Physics, Vol. 24, Issue 2
  • DOI: 10.1088/1367-2630/ac4c0a

Physical reservoir computing—an introductory perspective
journal, May 2020


Magnetic Vortex State Stability, Reversal and Dynamics in Restricted Geometries
journal, June 2008


Artificial ‘spin ice’ in a geometrically frustrated lattice of nanoscale ferromagnetic islands
journal, January 2006

  • Wang, R. F.; Nisoli, C.; Freitas, R. S.
  • Nature, Vol. 439, Issue 7074
  • DOI: 10.1038/nature04447

Comparison of Spin-Wave Modes in Connected and Disconnected Artificial Spin Ice Nanostructures Using Brillouin Light Scattering Spectroscopy
journal, June 2021

  • Chaurasiya, Avinash Kumar; Mondal, Amrit Kumar; Gartside, Jack C.
  • ACS Nano, Vol. 15, Issue 7
  • DOI: 10.1021/acsnano.1c02537

Selective and fast plasmon-assisted photo-heating of nanomagnets
journal, January 2019

  • Pancaldi, Matteo; Leo, Naëmi; Vavassori, Paolo
  • Nanoscale, Vol. 11, Issue 16
  • DOI: 10.1039/C9NR01628G

Dynamic dependence to domain wall propagation through artificial spin ice
journal, March 2017


Rewritable artificial magnetic charge ice
journal, May 2016


Re-visiting the echo state property
journal, November 2012


Sculpting the spin-wave response of artificial spin ice via microstate selection
journal, December 2019


Realization of ground state in artificial kagome spin ice via topological defect-driven magnetic writing
journal, November 2017


New results on recurrent network training: unifying the algorithms and accelerating convergence
journal, May 2000

  • Atiya, A. F.; Parlos, A. G.
  • IEEE Transactions on Neural Networks, Vol. 11, Issue 3
  • DOI: 10.1109/72.846741

On the Theory of Ferromagnetic Resonance Absorption
journal, January 1948


Magnetization dynamics of nanoscale magnetic materials: A perspective
journal, November 2020

  • Barman, Anjan; Mondal, Sucheta; Sahoo, Sourav
  • Journal of Applied Physics, Vol. 128, Issue 17
  • DOI: 10.1063/5.0023993

Temporal data classification and forecasting using a memristor-based reservoir computing system
journal, October 2019


Excitation of Whispering Gallery Magnons in a Magnetic Vortex
journal, March 2019


Voltage-controlled superparamagnetic ensembles for low-power reservoir computing
journal, May 2021

  • Welbourne, A.; Levy, A. L. R.; Ellis, M. O. A.
  • Applied Physics Letters, Vol. 118, Issue 20
  • DOI: 10.1063/5.0048911

Gyration mode splitting in magnetostatically coupled magnetic vortices in an array
journal, October 2010


The 2021 Magnonics Roadmap
journal, March 2021


Nanomagnonics with artificial spin ice
journal, June 2021


Resistive switching materials for information processing
journal, January 2020


Low power continuous-wave all-optical magnetic switching in ferromagnetic nanoarrays
conference, October 2022

  • Stenning, Kilian D.; Xiao, Xiaofei; Holder, Holly H.
  • Active Photonic Platforms (APP) 2022
  • DOI: 10.1117/12.2633356