Topic: "kernel-polynomial-method"
joselado/dmrgpy
DMRGPy is a Python library to compute quasi-one-dimensional spin chains and fermionic systems using matrix product states with DMRG as implemented in ITensor. Most of the computations can be performed both with DMRG and exact diagonalization for small systems, which allows one to benchmark the results.
Language: C++ - Size: 41.9 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 101 - Forks: 20
joselado/quantum-honeycomp
Package to perform tight binding calculation in tight binding models, with a friendly user interface
Language: Python - Size: 46.4 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 39 - Forks: 17
joselado/pygra
Python library to compute different properties of tight binding models
Language: Python - Size: 8.93 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 27 - Forks: 21
stdogpkg/emate
eMaTe can estimate the spectral density and trace functions even in matrices or graphs (undirected or directed) with million of nodes. (kernel polynomial method and SLQ)
Language: Python - Size: 262 KB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 10 - Forks: 2
joselado/kpmpy
Python package implementing the kernel polynomial method
Language: Python - Size: 234 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 2
piskunow/kpm-tools
Toolkit with Kernel Polynomial Method based modules for quantum physics simulations.
Language: Python - Size: 2.24 MB - Last synced at: 24 days ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0
JefferyWangSH/kpm-bdg
Kernel polynomial method (KPM) applied to BdG Hamiltonian.
Language: Python - Size: 5.86 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0
masaico/TB_models
Numerical methods for tight-binding models --CPA, KPM, Chebyshev expansion
Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
