Uncertainty Propagation in Quantitative Magnetic Force Microscopy Using a Monte-Carlo Method

A Monte-Carlo (MC)-type method is utilized for the propagation of uncertainties in quantitative magnetic force microscopy (qMFM). In qMFM, quantitative magnetic field distributions are inferred from magnetic force microscopy (MFM) raw data using a calibration of the instrument point spread function...

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Published inIEEE transactions on magnetics Vol. 58; no. 5; pp. 1 - 8
Main Authors Marschall, Manuel, Sievers, Sibylle, Schumacher, Hans Werner, Elster, Clemens
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Calibration
Magnetic fields
Magnetic force microscopy
magnetic force microscopy (MFM)
Magnetic multilayers
Magnetic resonance imaging
Magnetism
Mathematical models
Measurement uncertainty
Microscopy
Monte Carlo (MC) methods
Monte Carlo simulation
Phase measurement
Point spread functions
Propagation
Quantitative analysis
Side effects
Uncertainty
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ISSN0018-9464
1941-0069
DOI10.1109/TMAG.2022.3153176

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Abstract A Monte-Carlo (MC)-type method is utilized for the propagation of uncertainties in quantitative magnetic force microscopy (qMFM). In qMFM, quantitative magnetic field distributions are inferred from magnetic force microscopy (MFM) raw data using a calibration of the instrument point spread function and a subsequent inversion process. The two stages of calibration and measurement may be subject to a variety of uncertainties that naturally arise in practice. Identifying these sources of uncertainties and quantifying their impact on the reconstruction of the measurand is crucial for reliable quantitative studies of nanomagnetic materials and devices. So far, the propagation of variance method has been applied to determine the uncertainty budget for a complete calibration and measurement process. In this work, we are able to improve the uncertainty description in terms of structure and magnitude by application of an MC method. We demonstrate the importance of correlations and show possible side effects of model linearizations.
AbstractList A Monte-Carlo (MC)-type method is utilized for the propagation of uncertainties in quantitative magnetic force microscopy (qMFM). In qMFM, quantitative magnetic field distributions are inferred from magnetic force microscopy (MFM) raw data using a calibration of the instrument point spread function and a subsequent inversion process. The two stages of calibration and measurement may be subject to a variety of uncertainties that naturally arise in practice. Identifying these sources of uncertainties and quantifying their impact on the reconstruction of the measurand is crucial for reliable quantitative studies of nanomagnetic materials and devices. So far, the propagation of variance method has been applied to determine the uncertainty budget for a complete calibration and measurement process. In this work, we are able to improve the uncertainty description in terms of structure and magnitude by application of an MC method. We demonstrate the importance of correlations and show possible side effects of model linearizations.
Author Marschall, Manuel
Schumacher, Hans Werner
Sievers, Sibylle
Elster, Clemens
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Snippet A Monte-Carlo (MC)-type method is utilized for the propagation of uncertainties in quantitative magnetic force microscopy (qMFM). In qMFM, quantitative...
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SubjectTerms Calibration
Magnetic fields
Magnetic force microscopy
magnetic force microscopy (MFM)
Magnetic multilayers
Magnetic resonance imaging
Magnetism
Mathematical models
Measurement uncertainty
Microscopy
Monte Carlo (MC) methods
Monte Carlo simulation
Phase measurement
Point spread functions
Propagation
Quantitative analysis
Side effects
Uncertainty
Title Uncertainty Propagation in Quantitative Magnetic Force Microscopy Using a Monte-Carlo Method
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