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Design of a spintronic synapse for advanced neuromorphic circuits
Research & development - Leuven | More than two weeks ago
Design and modelling of an artificial synapse in the larger goal of building advanced spintronic neural networks and spin-wave-based computation
Bio-inspired
neuromorphic computing promises to realize the transformative potential of
Artificial Intelligence (AI) by providing a path for the implementation of
ultra-low power and advanced AI. Spintronic and magnetic materials are
particularly attractive for neuromorphic computing owing to their small
footprint, high endurance and low power consumption. Building on past work1
which involved the design of an artificial neuron that was the first to
demonstrate multiple advanced cognitive abilities, here we propose to design a
compatible spintronic synapse. A synapse is an adaptive memory element in the
brain that stores information and learns new knowledge. This project involves
the design of a novel artificial synapse that utilizes (i) magnetic domain
walls and (ii) spin waves and leverages recently discovered coupling between
the two2. This artificial synapse will be an important step forward
in the larger goal of building advanced spintronic neural networks and
spin-wave-based computation. The project will involve atomistic and
micromagnetic simulations of the materials and devices that will be carried out
by the Master’s student.
REFERENCES
1. P. Jadaun, C. Cui and J. A. Incorvia, Design of self-adaptive oscillating neurons using electrically reconfigurable skyrmion lattices, Preprint arXiv:2010.15748, under review.
2. J. Han, P. Zhang, J. T. Hou, S. A. Siddiqui and L. Liu, "Mutual control of coherent spin waves and magnetic domain walls in a magnonic device," Science, vol. 366, p. 1121–1125, 2019.Type of project: Thesis
Duration: 1 Academic year
Required degree: Master of Engineering Science, Master of Science
Required background: Nanoscience & Nanotechnology, Physics, Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Priyamvada Jadaun (Priyamvada.Jadaun@imec.be)
Only for self-supporting students.