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Hgy's Projects

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"Deep Learning and Quantum Programming" Spring School @ Song Shan Lake

strain-dirac icon strain-dirac

Calculates properties of superconducting or non-superconducting 2D Dirac electrons in an arbitrary quasi-1D vector potential

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Jupyter notebook implementations of Gaussian mixture model and Gaussian process written for Machine Learning in Condensed Matter Physics Conference at Donostia International Physics Center (DIPC)

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Heavyweight plotting tools for ab initio calculations

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surface green function calculation

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Tight binding package. Define effective tight binding systems (instances of the class tb.sc.SuperCell) and create the tight binding matrix using the method tbmat(). Several common tight binding models are predefined in the submodule define.

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landau_levels_of TBG

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Tight-Binding Modeling for Materials at Mesoscale

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A C++ library for solving second-quantized Hamiltonians

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Semi-empirical tight-binding computation of the electronic structure of semiconductors

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Interaction-driven topological superconductivity

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Topological Superconductors - Notebooks for an introductory course

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Course - Topology in CM. Include assignments, notes and technical details

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The goal is to implement an algorithm to compute persistence homology with coefficients in the field Z2, and to test it on various filtrations.

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Calculate bandstructures, DOS, spectral function, chern number and Z2 invariant from a given tight-binding Hamiltonian

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Compute Chern number, Z2 number, Berryphase, Slab, and Fermi arc in 2-bands periodic systems with Hamiltonian formulation.

tutorials icon tutorials

introduction to machine learning notebooks for physics education researchers

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Unfolding code using wannier functions

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Python program to evaluate off-resonance Raman activity using VASP code as the backend.

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