The electron dynamics in the unoccupied states of the Weyl semimetal PtBi2 is studied by time- and angle-resolved photoemission spectroscopy (TR-ARPES). The measurement's result is the photoemission intensity I as a function of at least four parameters: the emission angle and kinetic energy of the photoelectrons, the time delay between pump and probe laser pulses, and the probe laser photon energy that needs to be varied to access the full three-dimensional Brillouin zone of the material. The TR-ARPES results are reported in an accompanying paper. Here we focus on the technique of using k-means, an unsupervised machine learning technique, in order to discover trends in the four-dimensional data sets. We study how to compare the electron dynamics across the entire data set and how to reveal subtle variations between different data sets collected in the vicinity of the bulk Weyl points.
@article{arxiv.2406.10551,
title = {Electron dynamics in a three-dimensional Brillouin zone analysed by machine learning},
author = {Paulina Majchrzak and Charlotte Sanders and Yu Zhang and Andrii Kuibarov and Oleksandr Suvorov and Emma Springate and Iryna Kovalchuk and Saicharan Aswartham and Grigory Shipunov and Bernd Büchner and Alexander Yaresko and Sergey Borisenko and Philip Hofmann},
journal= {arXiv preprint arXiv:2406.10551},
year = {2025}
}