Regensburg 2025 – wissenschaftliches Programm
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O: Fachverband Oberflächenphysik
O 67: Ultrafast Electron Dynamics II
O 67.9: Vortrag
Mittwoch, 19. März 2025, 17:00–17:15, H11
A machine-learning approach to understanding ultrafast carrier dynamics in the 3D Brillouin zone of PtBi2 — Paulina Majchrzak1, Charlotte Sanders2, Yu Zhang2, Andrii Kuibarov3, Oleksandr Suvorov3, Tami Meyer1, Gesa Siemann1, Emma Springate2, Iryna Kovalchuk3,4, Saicharan Aswartham3, Grigory Shipunov3, Bernd Büchner3, Sergey Borisenko3, and •Philip Hofmann1 — 1Department of Physics and Astronomy, Aarhus University, DK — 2Central Laser Facility, Harwell, UK — 3IFW Dresden, Germany — 4Kyiv Academic University, UA
We examine the electron dynamics of the type-I Weyl semimetal PtBi2 by time- and angle-resolved photoemission spectroscopy. By varying the probe photon energy over a wide range, we are able to explore differences throughout the three-dimensional Brillouin zone. For these experiments, the photoemission intensity is measured as a function of emission angle, electron kinetic energy, time delay and probe photon energy. In order to discover trends in this multi-dimensional data set, we apply k-means, an unsupervised machine learning technique. This reveals kz-dependent differences in dynamics–in particular, we observe dynamics that are faster in the parts of the Brillouin zone that host most of the bulk Fermi surface than in parts close to the Weyl points.
Keywords: ultrafast electron dynamics; machine learning; Weyl semimetal