Chaotic proliferation of relativistic domain walls for reservoir computing
Abstract Magnetic domain walls in antiferromagnets have been proposed as key components for faster conventional information processing, thanks to their enhanced stability and ultrafast propagation. However, how non-conventional computing methods like reservoir computing might take advantage of these properties remains an open question. In this work, we show how complex domain wall patterns can form through the proliferation of multiple-domain walls from the energy stored in a single seed domain wall driven to move at a high speed close to the relativistic limit. We demonstrate that the resulting magnetic texture, consisting of up to hundreds of domain walls with an overall conserved topological charge as the initial seed domain wall, can possess chaotic spatio-temporal dynamics depending on the strength of staggered spin–orbit field induced via applied current. These findings allow us to design a multiple-domain-wall reservoir with high short-term memory and nonlinearity with respect to spin–orbit field inputs, that is suitable for ultrafast, energy-efficient, and non-conventional reservoir computing.
Authors
- R. M. Otxoa (ORCID: https://orcid.org/0000-0003-1534-4159)
- R.W. Chantrell (ORCID: https://orcid.org/0000-0001-5410-5615)
- Masahito Mochizuki (ORCID: https://orcid.org/0000-0002-0128-0580)
- J. A. Vélez (ORCID: https://orcid.org/0000-0001-5213-7912)
- Gen Tatara (ORCID: https://orcid.org/0000-0003-0642-8609)
- Mu-Kun Lee (ORCID: https://orcid.org/0009-0003-8029-8256)
- Richard F. L. Evans (ORCID: https://orcid.org/0000-0002-2378-8203)
- D. Laroze (ORCID: https://orcid.org/0000-0002-6487-8096)
- U. Atxitia
- J. B. Alexander Ross (ORCID: https://orcid.org/0000-0002-5547-6618)
- Paul-Iulian Gavriloaea
Institutions
- Waseda University (JP)
- University of the Basque Country (ES)
- University of Tarapacá (CL)
- Hitachi (United Kingdom) (GB)
- Polymat (ES)
- Pioneer (Japan) (JP)
- Instituto de Ciencia de Materiales de Madrid (ES)
- RIKEN Center for Emergent Matter Science (JP)
- Donostia International Physics Center (ES)
- University of York (GB)
Publication Details
- Journal
- npj Spintronics
- Published
- 2025-04-12
- DOI
- https://doi.org/10.1038/s44306-025-00079-y
- Citations
- 2
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- European Commission
- Waseda University
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- European Regional Development Fund
- Agencia Estatal de Investigación
- Core Research for Evolutional Science and Technology
- European Social Fund