Year: 2020
Type: article
Abstract: The reservoir computing paradigm posits that complex physical systems can be used to simplify pattern recognition tasks and nonlinear signal prediction. We show that random topological magnetic textures pinned by grain inhomogeneities demonstrate desirable dynamical responses for the implementation of reservoir computing as applied to ac current pulses. By harnessing the complex resistance or magnetization responses exhibited by random magnetic skyrmion textures to demonstrate simple pattern recognition, we explain how spintronics systems offer an advantage in the search for an ideal reservoir computer. The dynamical properties of compact skyrmion fabrics, coupled with their CMOS integrability operating on similar length and timescales, open the door for skyrmion-based reservoir computing applications.
Source: Physical Review Applied
Authors: D. Pinna, G. Bourianoff, K. Everschor-Sitte
Institutions: Johannes Gutenberg University Mainz, Intel (United States)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W2902888152