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Spin wave computing using pre-recorded magnetization patterns

We propose a novel type of spin wave computing device, based on a bilayer structure that includes a “bias layer” made from a hard magnetic material and a “propagation layer” made from a magnetic material with low damping, for example, yttrium garnet or permalloy. The bias layer maintains a stable pr...

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Published in:Journal of applied physics 2022-10, Vol.132 (15)
Main Authors: Rivkin, Kirill, Montemorra, Michael
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Language:English
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description We propose a novel type of spin wave computing device, based on a bilayer structure that includes a “bias layer” made from a hard magnetic material and a “propagation layer” made from a magnetic material with low damping, for example, yttrium garnet or permalloy. The bias layer maintains a stable pre-recorded magnetization pattern, which generates a bias field with a desired spatial dependence, which in turn sets the equilibrium magnetization inside the propagation layer. When an external source applies an RF field to the propagation layer, excited spin waves scatter on the magnetization's inhomogeneities resulting in complex interference behavior. This scattering interference can be utilized to perform a variety of mathematical operations including Vector-Matrix multiplication. The spatial dependence of such magnetization patterns can be estimated via perturbation theory.
doi_str_mv 10.1063/5.0096192
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subjects Applied physics
Bias
Computation
Damping
Ferrous alloys
Interference
Magnetic alloys
Magnetic materials
Magnetization
Magnons
Mathematical analysis
Perturbation theory
Scatter propagation
Wave propagation
Yttrium
title Spin wave computing using pre-recorded magnetization patterns
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