Statistical learning of engineered topological phases in the kagome superlattice of AV3Sb5

Thomas Mertz, Paul Wunderlich, Shinibali Bhattacharyya, Francesco Ferrari, Roser Valentí

npj Computational Materials · 2022 · 10 citations · 36 references

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Abstract

Abstract Recent experimental findings have reported the presence of unconventional charge orders in the enlarged (2 × 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 higher-order topological phases that may be realized by appropriately manipulating the currently known systems.

References

36