Seeing moiré: Convolutional network learning applied to twistronics

Seeing moiré: Convolutional network learning applied to twistronics

Moiré patterns made of two-dimensional (2D) materials represent highly tunable electronic Hamiltonians, allowing a wide range of quantum phases to emerge in a single material. Current modeling techniques for moiré electrons require significant technical work specific to each material, impeding large...

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Bibliographic Details
Main Authors: Diyi Liu, Mitchell Luskin, Stephen Carr
Format: Article
Language:English
Published: American Physical Society 2022-12-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/PhysRevResearch.4.043224

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