Machine learning algorithms for many-body quantum systems
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Updated
Sep 4, 2024 - Python
Machine learning algorithms for many-body quantum systems
Quantum Lattice Model Simulator Package
Basics on Exact Diagonalization
Exact diagonalization, Lehmann's representation, Two-particle Green's functions
Lanczos diagonalization of a Heisenberg-like Hamiltonian in Julia.
Exact diagonalization library for general models
A package to simplify working with symmetry-adapted quantum many-body bases. Provides a good foundation for writing custom exact diagonalization and variational Monte Carlo software
Random Integrators for many-body quantum systems
A Julia code for performing exact diagonalization of fractional quantum Hall systems
A quantum operator algebra domain-specific language and exact diagonalization toolkit for C++11/14/17
C++ library for Exact Diagonalization of quantum many-body systems
An Exact Diagonalization Code for the 1D & 2D Hubbard Model
User-friendly exact diagonalization package written in Haskell. Can treat systems of up to 𝒪(42) spins!
Exact diagonalization for finite quantum systems
Code for exact diagonalization of BoseHubbard hamiltonian
Exact Diagonalization for Hubbard model/Tight-binding model by MatheMatica
Equilibrium ED solver for finite fermionic models that can compute Keldysh Green's functions
Quick and dirty TRIQS wrapper around the Pomerol exact diagonalization library
Python bindings for libcommute
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