Application of Edge Detection Techniques to ARPES Data Analysis*

Well known edge detection and similar image analysis techniques can be applied to Angle Resolved Photoemission Spectroscopy (ARPES) data to achieve a result similar to that achieved through other, more computationally intensive methods and with more generality. Without applying any form of image analysis, the interpretation of ARPES data is left to the eyes of researchers and can be tricky and unreliable due to many sources of noise and distortion from the experimental processes, as a result, some of the finer, defining details required to classify a material can be missed. By applying these edge detection techniques, we are able to highlight key features such as distinct clustered bands and other fine details which may have otherwise been obscured. Here we show the implementations of various well known image processesing techniques applied to ARPES data and how they not only aid the interpretation of results, but can be looked upon as the stepping stones to more efficient data processing techniques and potential automation of the classification of quantum materials through analysis of ARPES data.