Kernel Polynomial Method implementation using Chebyshev expansion for disordered lattices.
-
Updated
Nov 20, 2018 - Fortran
Kernel Polynomial Method implementation using Chebyshev expansion for disordered lattices.
Tanslate a TB model into Hcircuit Model (Spice Model) and manipulate it
Quantum methods of solid state physics program showing band structure od 2-dimentional carbon crystal - graphene. It's calculated using method of tight binding (TB).
Hop.jl has been renamed to HopTB.jl and moved to https://github.com/HopTB/HopTB.jl
DeePTB: A deep learning package for tight-binding approach with ab initio accuracy.
Java class files (from Maven project) demonstrating tight coupling, loose coupling with interface and abstract class, and loose coupling with Spring Framework
Simple code to obtain the dispersion curve and z component of spin-spin correlation for a 1D Tight Binding model.
LTB-Symm is a publicly available code that does two things: large scale tight-binding (LTB) calculation of 2D materials, and checks topological symmetries (Symm) of their wave functions.
A repo containing code for TSC (topological superconductivity) simulations.
Toolkit with Kernel Polynomial Method based modules for quantum physics simulations.
Codes to predict DoS of a polymer chain in vacuum with Python Tightbinding (Huckel model)
🎲⛓👉🧪 Markov Chain Monte Carlo on the Falikov-Kimball model.
TiPSi builder module as a pure Python package for ease of installation
Here we are trying to model & simulate the band structures (tightbinding, FDTD, PWE (plane wave expansion), Density Functional theory (DFT), ...)
FORTRAN Code to simulate the effects of impurities embedded in or adsorbed on superconducting hosts.
StraWBerryPy (Single-poinT and local invaRiAnts for Wannier Berriologies in Python) is a Python package to calculate topological invariants and quantum-geometrical quantities in non-crystalline topological insulators
Tools for general Tight Binding systems
Python package to model and calculate electronic properties of materials using atomic configurations from experiments or computer simulations (e.g classical molecular dynamics) via tight-binding formulation
Material for the DFTB+ school in Daresbury 2022
Add a description, image, and links to the tight-binding topic page so that developers can more easily learn about it.
To associate your repository with the tight-binding topic, visit your repo's landing page and select "manage topics."