SchNetPack - Deep Neural Networks for Atomistic Systems
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Updated
Sep 30, 2024 - Python
SchNetPack - Deep Neural Networks for Atomistic Systems
Data mining for materials science
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Course on topology in condensed matter
WannierTools: An open-source software package for novel topological materials. Full documentation:
Scientific Python package for tight-binding calculations in solid state physics
Electronic structure Python package for post analysis and large scale tight-binding DFT/NEGF calculations
Matbench: Benchmarks for materials science property prediction
Mirror of the Kwant project https://gitlab.kwant-project.org/kwant/kwant
Exact diagonalization, Lehmann's representation, Two-particle Green's functions
Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
julia package for working with Keldysh Green's functions
Schrodinger-Poisson solver in 1D demonstrator
A Julia code for performing exact diagonalization of fractional quantum Hall systems
An Exact Diagonalization Code for the 1D & 2D Hubbard Model
Korringa-Kohn-Rostoker (multiple scattering theory/Green's function method) band structure calculation
Condensed matter physics, strong correlations, dual fermions
A collection of fortran modules and routines to support quantum many-body calculations, with a strong focus on Dynamical Mean-Field Theory
Semi-empirical tight-binding computation of the electronic structure of semiconductors
A Julia code for performing variational Monte Carlo (VMC) simulations of determinantal wave functions
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