About

Features

The main features of TBPLaS include:

Capabilities
- Modeling
  
  Models with arbitrary dimension, shape and boundary conditions
  
  Model replicating, reshaping, merging and splitting
  
  Clusters, nano-tubes, slabs and crystals
  
  Defects, impurities and disorders
  
  Hetero-structures, quasi-crystals, fractals
  
  Built-in support for Slater-Koster formulation and spin-orbital coupling
  
  Shipped with materials database (Graphene, phosphorene, antimonene, TMDC)
  
  Interfaces to Wannier90, LAMMPS, DeepH-pack and DeePTB
  
  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
  
  Arbitrary deformation with strain and stress
- Exact-diagonalization
  
  Band structure, density of states (DOS), wave functions
  
  Berry curvature, phase and topological invariants
  
  Spin texture
  
  Polarizability, dielectric function, optical (AC) conductivity
  
  Full diagonalization and selective diagonalization within specific energy range
  
  Non-orthogonal basis set
- 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
- Compatible Python/C++ modeling tools
- C++ core for performance-critical parts
- Hybrid parallelism based on MPI and OpenMP
- GPU computation based on CUDA
- Sparse matrices for reducing memory cost
- Lazy-evaluation technique to reduce unnecessary operations
- Interface to Netlib LAPACK, OpenBLAS, AMD AOCL and Intel MKL
User friendliness
- Intuitive object-oriented user APIs in both Python and C++
- Simple workflow with a lot of handy tools
- Transparent code architecture with detailed documentation
Security
- Detailed checking on input arguments with precise error message
- Top-down and bottom-up techniques for keeping data consistency

Gallery

Modeling

Properties calculation

bands — Band structure of TBG from diagonalization (left) and TBPM (right)

dos — Density of states of graphene from diagonalization and TBPM

ac_cond — Optical conductivity of graphene from diagonalization and TBPM

dos_mag — Landau levels in graphene under magnetic field

\(\mathbb{Z}_2\) topological invariant of bilayer bismuth

param_fit — Refitting of on-site energies and hopping terms from Wannier90 output

plasmon — Plasmon modes in twisted bilayer MoS2 Phys. Rev. B 105, 245415 (2022)

Local DOS in graphene nanobubbles Phys. Rev. B 109, 115420 (2024)

spin_texture — Spin texture of Kane-Mele model

spin_bands — Spin-resolved band structure of Kane-Mele model

berry_curvature — Berry curvature of Haldane model

wfc — Wave function propagation in graphene under deformation (f-j), scattering potential (k-o) and magnetic field (p-t)

../_images/h_chain.png — Export of 3D wave functions of hydrogen atomic chain

Citation

Please cite the follow paper(s) when using results from TBPLaS:

1. Li, Z. Zhan, X. Kuang, Y. Li and S. Yuan, TBPLaS: a Tight-Binding Package for Large-scale Simulation, Comput. Phys. Commun. 285, 108632 (2023)

License

TBPLaS is release under the BSD license 2.0, the complete content of which is as following:

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither the name of RU and WHU nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.