Acceleration of Ferromagnet Resonance (FMR) Measurements by Bayesian Experimental Design

Published

October 21, 2024

Author(s)

Dingbin Huang, Xiaojia Wang, Daniel Gopman

Abstract

Ferromagnetic resonance (FMR) is a broadly used dynamical measurement used to characterize a wide range of magnetic materials. Applied research and development on magnetic thin film materials is growing rapidly alongside a growing commercial appetite for magnetic memory and computing technologies. The ability to execute high-quality, fast FMR surveys of magnetic thin films is needed to meet the demanding throughput associated with rapid materials exploration and quality control. Here, we implement a sequential Bayesian experimental design developed by McMichael et al. [1] in a vector network analyzer-FMR setup to demonstrate an unexplored opportunity to accelerate FMR measurements. A systematic comparison is made between the sequential Bayesian measurement and the conventional measurement. Reduced uncertainties in linewidth and resonance frequency ranging from 40 % to 60 % are achieved with the Bayesian implementation. As the sequential Bayesian approach only decreases random errors, we evaluate how large systematic errors may limit the full advantage of the sequential Bayesian approach. This approach can be used to deliver gains in measurement speed by a factor of three or more and as a software add-on, has the flexibility to be added on to any FMR measurement system to accelerate materials discovery and quality control measurements, alike.

Citation

Review of Scientific Instruments

Pub Type

Journals

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Citation

Huang, D. , Wang, X. and Gopman, D. (2024), Acceleration of Ferromagnet Resonance (FMR) Measurements by Bayesian Experimental Design, Review of Scientific Instruments, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957807 (Accessed November 25, 2025)