Dataset supporting publication: "Remote-sensing based control of 3D magnetic fields using machine learning for in-operando applications".

The work demonstrates how the neural network enables to calibrate non-linear field responses when direct measurements at the position of interest are not feasible. The dataset includes code and processed data for reproducing the figures from the associated paper, and is intended to support further research in in-operando experiments that require high-precision field control.

For more information about the code and data, please refer to the readme.txt file. The published paper can be found here: doi.org/10.48550/arXiv.2411.10374 Requirements The code was executed with Python 3.12, the dependencies are listed in requirements.txt . Licenses The data is licensed under CC-BY, the code is licensed under MIT.