Nonlinear Magnons for Reservoir Computing in Reciprocal Space
Grant period
2022-10-01 - 2026-09-30
Funding body
European Union
Call number
HORIZON-CL4-2021-DIGITAL-EMERGING-01
Grant number
101070290
Identifier
G:(EU-Grant)101070290
Note: NIMFEIA aims to provide a hardware solution for brain-inspired computing using magnetic materials on the nanoscale combined with advanced spintronics technologies. It is based on the disruptive idea of computation in reciprocal space where nonlinear spin-wave interactions mediated by nontrivial spin textures, such as magnetic vortices, can be efficiently harnessed for reservoir computing tasks like pattern recognition and time series prediction with minimal pre-processing of input data. We will demonstrate the ground-breaking nature of our proposal by meeting four core objectives: (1) Demonstrating the core principles of reservoir computing using GHz-regime spin waves by quantifying and designing nonlinear scattering processes in reciprocal space (TRL 3); (2) Developing an experimental and scalable proof-of-concept device using industrially compatible processes (TRL 4); (3) Demonstrating the utility of the magnon reservoir on a selected pervasive real-world use case, namely gesture and feature recognition from radar data in autonomous driving scenarios (TRL 4-5); (3) Scaling the magnon reservoir to the THz regime by moving towards the edge of the Brillouin zone and through the use of antiferromagnetic materials. While Objectives 1-3 will focus on the validation of the novel technology in laboratory and industrially relevant environment, Objective 4 will provide the groundwork for pushing this technology towards THz frequency operation and 6G compatibility. NIMFEIA will lay the foundations for a new paradigm in nanomagnetic and spintronic technologies that go beyond traditional applications in binary storage and Boolean logic, radiofrequency signal processing, as well as field sensing. It will address major current technological challenges by proposing an energy-efficient computing scheme for edge computing using artificial intelligence.
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