Quantitative magnetic force microscopy (qMFM) is a technique to back out the magnetic structure of a sample from a measurement with MFM. The project objective is implement a reconstruction technique to evaluate the data and to package these tools in software that effectively hides complexity from the user.
In the very few cases where qMFM could be implemented so far, it provided otherwise inaccessible information on the magnetization mechanisms in thin films due to its high resolution, insensitivity to applied external fields, and calibrations validated independently of probe models. Here we seek to develop measurement techniques for reproducibly acquiring MFM data that can be evaluated quantitatively, to design numerical tools for this evaluation, and to package these tools in software that effectively hides complexity from the user.
We contribute algorithms for finding a correct and optimal calibration function for the implementation of qMFM, and performing the necessary image data deconvolutions. This involves taking into account priors such as e.g. knowledge of the negligible effect, far from the tip center, of high spatial frequency components. As a result of this work algorithms will be available to obtain optimal calibration functions from data obtained using highly accurate, automated measurement routines. Finally, our strategy for disseminating the knowledge obtained in this project is the establishment of web-based a framework for the effective utilization of these tools, including visualization capability and comprehensive tutorials.