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4 October 2022 A data-driven approach for solving the vortex-based spin-torque oscillator dynamics as a new tool for exploring neuromorphic applications (Conference Presentation)
Chloé Chopin, Simon de Wergifosse, Flavio Abreu Araujo
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Proceedings Volume PC12205, Spintronics XV; PC122050P (2022) https://doi.org/10.1117/12.2632073
Event: SPIE Nanoscience + Engineering, 2022, San Diego, California, United States
Abstract
A semi-analytical method (data-driven model) is used to predict the dynamics of a Spin-Torque Vortex Oscillator (STVO). This model relies on an improved analytical model based on the Thiele equation approach and micromagnetic simulations. The improved analytical model shows that the Ampère-Oersted field cannot be neglected and it describes quantitatively the STVO dynamics only in the resonant regime when the data-driven model allows to describe it in the steady-state oscillating regime as well. In addition, the model is 2.1 million time faster than simulations. It can be used to simulate the spin-diode effect and functionalize the STVOs for neuromorphic applications.
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Chloé Chopin, Simon de Wergifosse, and Flavio Abreu Araujo "A data-driven approach for solving the vortex-based spin-torque oscillator dynamics as a new tool for exploring neuromorphic applications (Conference Presentation)", Proc. SPIE PC12205, Spintronics XV, PC122050P (4 October 2022); https://doi.org/10.1117/12.2632073
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KEYWORDS
Oscillators
Data modeling
Computer simulations
Magnetism
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