Machine-learning approach to understanding ultrafast carrier dynamics in the three-dimensional Brillouin zone of PtBi_{2}

Machine-learning approach to understanding ultrafast carrier dynamics in the three-dimensional Brillouin zone of PtBi_{2}

Using time- and angle-resolved photoemission spectroscopy, we examine the unoccupied electronic structure and electron dynamics of the type-I Weyl semimetal PtBi_{2}. Using the ability to change the probe photon energy over a wide range, we identify the predicted Weyl points in the unoccupied three-...

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Bibliographic Details
Main Authors: Paulina Majchrzak, Charlotte Sanders, Yu Zhang, Andrii Kuibarov, Oleksandr Suvorov, Emma Springate, Iryna Kovalchuk, Saicharan Aswartham, Grigory Shipunov, Bernd Büchner, Alexander Yaresko, Sergey Borisenko, Philip Hofmann
Format: Article
Language:English
Published: American Physical Society 2025-01-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/PhysRevResearch.7.013025
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Summary:Using time- and angle-resolved photoemission spectroscopy, we examine the unoccupied electronic structure and electron dynamics of the type-I Weyl semimetal PtBi_{2}. Using the ability to change the probe photon energy over a wide range, we identify the predicted Weyl points in the unoccupied three-dimensional band structure and we discuss the effect of k_{⊥} broadening in the normally unoccupied states. We characterize the electron dynamics close to the Weyl points and in other parts of three-dimensional Brillouin zone using k-means, an unsupervised machine-learning technique. This reveals distinct differences—in particular, that the electron dynamics close to the Weyl points are slower than in Brillouin zone regions close to the bulk Fermi surface.
ISSN:2643-1564

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