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Found 4 papers, 1 papers with code
Deep learning extraction of band structure parameters from density of states: a case study on trilayer graphene
Next, we use the fast and accurate predictions from the trained network to automatically determine tight-binding parameters directly from experimental data, with extracted parameters being in a good agreement with values in the literature.
Area-law entangled eigenstates from nullspaces of local Hamiltonians
Eigenstate thermalization in quantum many-body systems implies that eigenstates at high energy are similar to random vectors.
Quantum Physics Disordered Systems and Neural Networks Quantum Gases Statistical Mechanics
Quantum annealing initialization of the quantum approximate optimization algorithm
This motivates studies of the optimization landscape and search for heuristic ways of parameter initialization.
Quantum Physics Disordered Systems and Neural Networks Statistical Mechanics Computational Physics
Thouless Energy Across Many-Body Localization Transition in Floquet Systems
We investigate the scaling of Thouless energy across the many-body localization (MBL) transition in a Floquet model.
Disordered Systems and Neural Networks Mesoscale and Nanoscale Physics Strongly Correlated Electrons Quantum Physics
