Measurement-driven Langevin modeling of superparamagnetic tunnel junctions

Published

July 23, 2024

Author(s)

Liam Pocher, Temitayo Adeyeye, Sidra Gibeault, Philippe Talatchian, Ursula Ebels, Daniel Lathrop, Jabez J. McClelland, Mark Stiles, Advait Madhavan, Matthew Daniels

Abstract

Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing qualitatively accurate analog dynamics of these devices will be important as the technology scales up. Here we present results using a one-dimensional overdamped Langevin equation that captures statistical properties of measured time traces, including voltage histograms, drift and diffusion characteristics as measured with Kramers-Moyal coefficients, and dwell times distributions. While common macrospin models are more physically-motivated magnetic models than the Langevin model, we show that for the device measured here, they capture even fewer of the measured experimental behaviors.

Citation

Physical Review Applied

Volume

22

Issue

1

Pub Type

Journals

Download Paper

https://doi.org/10.1103/PhysRevApplied.22.014057

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Citation

Pocher, L. , Adeyeye, T. , Gibeault, S. , Talatchian, P. , Ebels, U. , Lathrop, D. , McClelland, J. , Stiles, M. , Madhavan, A. and Daniels, M. (2024), Measurement-driven Langevin modeling of superparamagnetic tunnel junctions, Physical Review Applied, [online], https://doi.org/10.1103/PhysRevApplied.22.014057, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957009 (Accessed October 6, 2025)