https://github.com/deepmodeling/tbplas

Repository of TBPLaS (tight-binding package for large-scale simulation)
https://github.com/deepmodeling/tbplas

condensed-matter-physics solid-state-physics tight-binding

Last synced: about 2 months ago
JSON representation

Repository of TBPLaS (tight-binding package for large-scale simulation)

• Host: GitHub
• URL: https://github.com/deepmodeling/tbplas
• Owner: deepmodeling
• License: other
• Created: 2024-02-29T03:21:24.000Z (7 months ago)
• Default Branch: master
• Last Pushed: 2024-04-11T02:16:51.000Z (5 months ago)
• Last Synced: 2024-07-22T00:46:11.814Z (about 2 months ago)
• Topics: condensed-matter-physics, solid-state-physics, tight-binding
• Homepage: http://www.tbplas.net
• Size: 23.7 MB
• Stars: 6
• Watchers: 9
• Forks: 4
• Open Issues: 4
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.rst

Awesome Lists containing this project

• deepmodeling-projects - GitHub

README

        
Introduction

============

TBPLaS (Tight-Binding Package for Large-scale Simulation) is a package for building and solving

tight-binding models, with emphasis on handling large systems. TBPLaS implements exact

diagonalization-based methods, the tight-binding propagation method (TBPM), kernel polynomial

method (KPM), and Green's function method. Sparse matrices, Cython/FORTRAN extensions and hybrid

OpenMP+MPI parallelization are utilized for optimal performance on modern computers. The main

features of TBPLaS include:

* Capabilities

    * Modeling

        * Models with arbitrary dimesion, shape and boundary conditions

        * Clusters, nano-tubes, slabs and crystals

        * Defects, impurities and disorders

        * Hetero-structures, quasicrystal, fractals

        * Built-in support for Slater-Koster formulation and spin-orbital coupling

        * Shipped with materials database (Graphene, phosphorene, antimonene, TMDC)

        * Interfaces to Wannier90 and LAMMPS

        * Tools for fitting on-site energies and hopping integrals

        * Support for analytical Hamiltonian

    * Fields and strains

        * Homogeneous magnetic field via Peierls substitution

        * User-defined electric field

        * Arbitary deformation with strain and/or stress

    * Exact-diagonalization

        * Band structure, density of states (DOS), wave functions, topological invariants, spin textures

        * Polarizability, dielectric function, optical (AC) conductivity

    * Tight-binding propagation method (TBPM)

        * DOS, LDOS and carrier density

        * Optical (AC) conductivity and absorption spectrum

        * Electronic (DC) conductivity and time-dependent diffusion coefficient

        * Carrier velocity, mobility, elastic mean free path, Anderson localization length 

        * Polarization function, response function, dielectric function, energy loss function

        * Plasmon dispersion, plasmon lifetime and damping rate

        * Quasi-eigenstate and real-space charge density

        * Propagation of time-dependent wave function

    * Kernel polynomial method

        * Electronic (DC) and Hall Conductivity  

    * Recursive Green's function method

        * Local density of states (LDOS)

* Efficiency

    * Cython (C-Extensions for Python) and FORTRAN for performance-critical parts

    * Hybrid parallelism based on MPI and OpenMP

    * Sparse matrices for reducing memory cost

    * Lazy-evaluation techniques to reduce unnecessary operations

    * Interfaced to Intel MKL (Math Kernel Library)

* User friendliness

    * Intuitive object-oriented user APIs (Application Programming Interface) in Python with type hints

    * Simple workflow with a lot of handy tools

    * Transparent code architecture with detailed documentation

* Security

    * Detailed checking procedures on input arguments

    * Carefully designed exception handling with precise error message

    * Top-down and bottom-up (observer pattern) techniques for keeping data consistency

Installation

------------

See *INSTALL.rst* for the installation guides.

Tutorials

---------

Some examples demonstrating the features of TBPLaS can be found under *examples* directory.

More detailed tutorials can be found in the online documentation.

Documentation

-------------

The documentation is available online at ``_.

Citation

--------

See *CITING.rst* for more details.

License

-------

TBPLaS is released under the BSD license. See *LICENSE.rst* for more details.