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arXiv · 2110.10171

Statistical learning of engineered topological phases in the kagome superlattice of AV$_3$Sb$_5$

Thomas Mertz·Paul Wunderlich·Shinibali Bhattacharyya·Francesco Ferrari·Roser Valentí
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Abstract

Recent experimental findings have reported the presence of unconventional charge orders in the enlarged ($2 \times 2$) unit-cell of kagome metals AV$_3$Sb$_5$ (A=K,Rb,Cs) and hinted towards specific topological signatures. Motivated by these discoveries, we investigate the types of topological phases that can be realized in such kagome superlattices. In this context, we employ a recently introduced statistical method capable of constructing topological models for any generic lattice. By analyzing large data sets generated from symmetry-guided distributions of randomized tight-binding parameters, and labeled with the corresponding topological index, we extract physically meaningful information. We illustrate the possible real-space manifestations of charge and bond modulations and associated flux patterns for different topological classes, and discuss their relation to present theoretical predictions and experimental signatures for the AV$_3$Sb$_5$ family. Simultaneously, we predict new higher-order topological phases that may be realized by appropriately manipulating the currently known systems.

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Thomas Mertz, Paul Wunderlich, Shinibali Bhattacharyya, Francesco Ferrari, Roser Valentí. 2022-01-31. Statistical learning of engineered topological phases in the kagome superlattice of AV$_3$Sb$_5$. https://doi.org/10.1038/s41524-022-00745-3

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