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In recent years, models based on Graph Convolutional Networks (GCN) have made significant strides in the field of graph data analysis. However, challenges such as over-smoothing and over-compression remain when handling large-scale and…

Machine Learning · Computer Science 2025-07-23 Binxiong Li , Xu Xiang , Xue Li , Binyu Zhao , Heyang Gao , Qinyu Zhao

We analytically compute the scanning tunneling microscopy (STM) signatures of integer-filled correlated ground states of the magic angle twisted bilayer graphene (TBG) narrow bands. After experimentally validating the strong-coupling…

Twisted graphene layers produce a moir\'e pattern (MP) structure with a predetermined wavelength for given twist angle. However, predicting the membrane corrugation amplitude for any angle other than pure AB-stacked or AA-stacked graphene…

Mesoscale and Nanoscale Physics · Physics 2015-06-22 M. Neek-Amal , P. Xu , D. Qi , P. M. Thibado , L. O. Nyakiti , V. D. Wheeler , R. L. Myers-Ward , C. R. Eddy , D. K. Gaskill , F. M. Peeters

Two-dimensional multi-layer materials with an induced moir\'e pattern, either due to strain or relative twist between layers, provide a versatile platform for exploring strongly correlated and topological electronic phenomena. While these…

Strongly Correlated Electrons · Physics 2025-05-27 Mohammed M. Al Ezzi , Albert Zhu , Daniel Bennett , Daniel T. Larson , Efthimios Kaxiras

Twisted bilayer graphene has a rich phase diagram, including superconductivity. Recently, an unexpected discovery has been the observation of superconductivity in non-twisted graphene bilayers and trilayers. In this Perspective, we give an…

Mesoscale and Nanoscale Physics · Physics 2023-05-29 Pierre A. Pantaleon , Alejandro Jimeno-Pozo , Hector Sainz-Cruz , Vo Tien Phong , Tommaso Cea , Francisco Guinea

We present a theoretical study of the local optical conductivity, plasmon spectra, and thermoelectric properties of twisted bilayer graphene (TBG) at different filling factors and twist angles $\theta$. Our calculations are based on the…

Mesoscale and Nanoscale Physics · Physics 2020-09-04 Pietro Novelli , Iacopo Torre , Frank H. L. Koppens , Fabio Taddei , Marco Polini

Twistronics is currently one of the most active research fields in condensed matter physics, following the discovery of correlated insulating and superconducting phases in twisted bilayer graphene (tBLG). Here, we present a magnonic…

Mesoscale and Nanoscale Physics · Physics 2020-09-17 Doried Ghader

Moir\'e superlattices in two-dimensional (2D) materials exhibit rich quantum phenomena, but ab initio modelling of these systems remains computationally prohibitive. Existing machine learning methods for accelerating density-functional…

Materials Science · Physics 2026-02-11 Zekun Lou , Alan M. Lewis , Mariana Rossi

The emergence of flat electronic bands and of the recently discovered strongly correlated and superconducting phases in twisted bilayer graphene crucially depends on the interlayer twist angle upon approaching the magic angle $\theta_M…

The effective theory for bilayer graphene (BLG), subject to parallel/in-plane magnetic fields, is derived. With a sizable magnetic field the trigonal warping becomes irrelevant, and one ends up with two Dirac points in the vicinity of each…

Mesoscale and Nanoscale Physics · Physics 2014-01-08 Bitan Roy , Kun Yang

We study a 2D continuum model of electronic transport in twisted bilayer graphene (TBG) at commensurate angles. We use two honeycomb potentials with the symmetries of graphene, either sharing a common origin (AA stacking) or shifted by a…

Mathematical Physics · Physics 2026-05-19 Tal Malinovitch

Two new Raman modes below 100 cm^-1 are observed in twisted bilayer graphene grown by chemical vapor deposition. The two modes are observed in a small range of twisting angle at which the intensity of the G Raman peak is strongly enhanced,…

Mesoscale and Nanoscale Physics · Physics 2013-08-16 Rui He , Ting-Fung Chung , Conor Delaney , Courtney Keiser , Luis A. Jauregui , Paul M. Shand , C. C. Chancey , Yanan Wang , Jiming Bao , Yong P. Chen

The combination of the traditional convolutional network (i.e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-encoder extracts the node attribute feature and the graph…

Computer Vision and Pattern Recognition · Computer Science 2021-08-13 Zhihao Peng , Hui Liu , Yuheng Jia , Junhui Hou

This paper describes a new method, HMM gauge likelihood analysis, or GLA, of detecting anomalies in discrete time series using Hidden Markov Models and clustering. At the center of the method lies the comparison of subsequences. To achieve…

Machine Learning · Computer Science 2020-09-22 Boris Lorbeer , Tanja Deutsch , Peter Ruppel , Axel Küpper

When twisted to angles near 1{\deg}, graphene multilayers provide a new window on electron correlation physics by hosting gate-tuneable strongly-correlated states, including insulators, superconductors, and unusual magnets. Here we report…

Semi-supervised clustering is an very important topic in machine learning and computer vision. The key challenge of this problem is how to learn a metric, such that the instances sharing the same label are more likely close to each other on…

Machine Learning · Computer Science 2015-01-27 Gang Chen

The electronic properties of junctions defined electrostatically on twisted bilayer graphene can be addressed theoretically using lattice models. Recent works have introduced minimal local orbital models to describe twisted bilayer graphene…

Mesoscale and Nanoscale Physics · Physics 2021-08-11 M. Alvarado , A. Levy Yeyati

We consider the superconducting and Mott-insulating states for the twisted bilayer graphene, modeled as two narrow-band system of electrons with appreciable intraatomic Coulomb interactions. The interaction induces kinetic exchange which…

Superconductivity · Physics 2018-08-29 Maciej Fidrysiak , Michał Zegrodnik , Józef Spałek

Superconductivity (SC) in twisted bilayer graphene (tBLG) has been explored by varying carrier concentrations, twist angles, and screening strength, with the aim of uncovering its origin and possible connections to strong electronic…

Mesoscale and Nanoscale Physics · Physics 2024-09-13 Ranit Dutta , Ayan Ghosh , Shinjan Mandal , K. Watanabe , T. Taniguchi , H. R. Krishnamurthy , Sumilan Banerjee , Manish Jain , Anindya Das

This work presents a novel approach to tabular data prediction leveraging graph structure learning and graph neural networks. Despite the prevalence of tabular data in real-world applications, traditional deep learning methods often…

Machine Learning · Computer Science 2023-05-26 Jay Chiehen Liao , Cheng-Te Li