Automating Electronic Transport Measurements at Low Temperatures and Performing Angle Resolved Photoemission Spectroscopy (ARPES) Data Analysis Using Python*

Low temperature electron transport experiments on low dimensional nanomaterials are ruled by exciting quantum effects. In order to extract meaningful information from these experiments, data must be collected and analyzed in an organized and efficient manner. We present a method using the Python programming language and open source libraries to control the acquisition, interactive visualization, and analysis of data from a closed cycle cryostat and different measurment instruments. Additionally, we show the data analysis of a large amount of ARPES data corresponding to the modulation of the intensity of C₆₀ band clusters with the incident photon energy.