Data analysis in LEEM and PEEM
MSc Tobias A. de Jong and MSc Pascal Dreher Leiden University (Netherlands) and University of Duisburg-Essen (Germany)
LEEM and PEEM experiments have advanced beyond pure imaging. This results in increasingly large and complex datasets, which require advanced data analysis before they can answer specific scientific questions.
In this tutorial, we will give several examples of modern image processing and analysis techniques for data and metadata generated in modern LEEM and PEEM experiments. Often the data analysis can be separated into a pipeline of multiple separate processing steps and we will identify the most common processing steps relevant to LEEM and PEEM. We will address basic techniques to process images, such as detector correction to convert raw detector counts to physically meaningful intensities, and image registration techniques to correct for sample drifts.
Next, we will discuss the analysis of two more complex, multi-dimensional datasets, the application of principal component analysis to (I(V)-LEEM) spectroscopy and the analysis needed to perform ultrafast vector microscopy in PEEM.
For participants who wish to have a look at some references and code beforehand:
– de Jong, Tobias A., et al. «Quantitative analysis of spectroscopic Low Energy Electron Microscopy data: High-dynamic range imaging, drift correction and cluster analysis.» Ultramicroscopy 213 (2020): 112913.
– Quantitative Data Analysis for spectroscopic LEEM, https://github.com/TAdeJong/LEEM-analysis
– Davis, Timothy J., et al. «Ultrafast vector imaging of plasmonic skyrmion dynamics with deep subwavelength resolution.» Science 368.6489 (2020). https://science.sciencemag.org/content/368/6489/eaba6415.abstract