FS-08 Ultrafast Skyrmions for Neuromorphic Computation
Creators: AJIN JOY
SREYAS SATHEESH
P. S. ANIL KUMAR
Publisher: name: IEEE
Year: 2025

The human brain processes information efficiently due to the dynamics of neurons and synapses,which can inspire effective artificial Spiking Neural Networks (SNN).Spintronic devices are ideal for neuromorphic computing,with skyrmions as effective information carriers due to their topological protection and particle-like nature.Ferrimagnet and antiferromagnet-based spintronics have previously enabled artificial synapses and neurons.We propose a ferromagnetic device (Ta3nmPt3nmCu0.65nmCo0.5nmPt1nm) that simulates artificial neurons and synapses ultrafast due to high-velocity skyrmions.Electrical pulses control skyrmion accumulation and dissipation, analogous to synaptic weight changes.Lateral Structure Inversion Asymmetry (SIA) enables field-free, energy-efficient switching.This device reproduces neuron and synapse functionalities with superior time scales, making ferromagnet-based skyrmions viable for ultrafast neuromorphic spintronics,capable of highly efficient cognitive tasks.References: 1. M.-K. Kim, Y. Park, I.-J. Kim, and J.-S. Lee, Emerging materials for neuromorphic devices and systems, iScience 23, 101846 (2020). 2. S. Fukami and H. Ohno, Perspective: Spintronic synapse for artificial neural network, Journal of Applied Physics 124, 151904 (2018). 3. M. Pfeiffer and T. Pfeil, Deep learning with spiking neurons: Opportunities and challenges, Frontiers in Neuro-science 12, (2018). 4. N. Nagaosa and Y. Tokura, Topological properties and dynamics of magnetic skyrmions, Nat Nanotechnol 8, 899, (2013). 5. M. Weißenhofer and U. Nowak, Diffusion of skyrmions: the role of topology and anisotropy, New Journal of Physics 22, 103059 (2020). 6. S. Lepadatu, Effect of inter-layer spin diffusion on skyrmion motion in magnetic multilayers, Sci Rep 9, 9592 (2019). 7. J. Grollier, D. Querlioz, K. Y. Camsari, K. Everschor- Sitte, S. Fukami, and M. D. Stiles, Neuromorphic spintronics, Nat Electron 3 (2020). 8. I. Dzyaloshinsky, A thermodynamic theory of “weak” ferromagnetism of antiferromagnetics, J. Phys.Chem.Sol. 4, 241 (1958).
The human brain processes information efficiently due to the dynamics of neurons and synapses,which can inspire effective artificial Spiking Neural Networks (SNN).Spintronic devices are ideal for neuromorphic computing,with skyrmions as effective information carriers due to their topological protection and particle-like nature.Ferrimagnet and antiferromagnet-based spintronics have previously enabled artificial synapses and neurons.We propose a ferromagnetic device (Ta3nmPt3nmCu0.65nmCo0.5nmPt1nm) that simulates artificial neurons and synapses ultrafast due to high-velocity skyrmions.Electrical pulses control skyrmion accumulation and dissipation, analogous to synaptic weight changes.Lateral Structure Inversion Asymmetry (SIA) enables field-free, energy-efficient switching.This device reproduces neuron and synapse functionalities with superior time scales, making ferromagnet-based skyrmions viable for ultrafast neuromorphic spintronics,capable of highly efficient cognitive tasks.References: 1. M.-K. Kim, Y. Park, I.-J. Kim, and J.-S. Lee, Emerging materials for neuromorphic devices and systems, iScience 23, 101846 (2020). 2. S. Fukami and H. Ohno, Perspective: Spintronic synapse for artificial neural network, Journal of Applied Physics 124, 151904 (2018). 3. M. Pfeiffer and T. Pfeil, Deep learning with spiking neurons: Opportunities and challenges, Frontiers in Neuro-science 12, (2018). 4. N. Nagaosa and Y. Tokura, Topological properties and dynamics of magnetic skyrmions, Nat Nanotechnol 8, 899, (2013). 5. M. Weißenhofer and U. Nowak, Diffusion of skyrmions: the role of topology and anisotropy, New Journal of Physics 22, 103059 (2020). 6. S. Lepadatu, Effect of inter-layer spin diffusion on skyrmion motion in magnetic multilayers, Sci Rep 9, 9592 (2019). 7. J. Grollier, D. Querlioz, K. Y. Camsari, K. Everschor- Sitte, S. Fukami, and M. D. Stiles, Neuromorphic spintronics, Nat Electron 3 (2020). 8. I. Dzyaloshinsky, A thermodynamic theory of “weak” ferromagnetism of antiferromagnetics, J. Phys.Chem.Sol. 4, 241 (1958).