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.. _pysktb:
Welcome to PySKTB!
========================
PySKTB (Python Slater Koster Tight Binding), is a python package for Slater-Koster tight binding calculations. pysktb provides tools for constructing and solving tight binding models, as well as for calculating various properties of the resulting electronic structure.
.. code-block:: python
import pysktb
# Define structure
structure = pysktb.Structure(
lattice=pysktb.Lattice([[1, 0, 0], [0, 10, 0], [0, 0, 10]], 1), #Lattice
atoms=[pysktb.Atom("Si", [0, 0, 0], orbitals=["s", "px"])], #s-px orbital
bond_cut={"SiSi": {"NN": 1.2}}, #NN cuttoff
)
# Construct Hamiltonian
hamiltonian = pysktb.Hamiltonian(
structure=structure,
inter={"Si": {"e_p": 0, "e_s": 0}, #SK Interactions
"SiSi": {"V_sss": -0.2, "V_sps": -0.05, "V_pps": 0.2}})
#Solve along k-path
path = [[0.5, 0.0, 0.0], [0.0, 0.0, 0.0], [-0.5, 0.0, -0.0]]
k_path, k_dist, k_pts = hamiltonian.get_kpts(path, 40) #Get k-path
evals, vecs = hamiltonian.solve_kpath(k_path, eig_vectors=True) #Solve for eigenvalues and eigenvectors
#Plot band structure
pysktb.Hamiltonian.plot_kproj(evals, vecs, k_dist, index=[0, 1])
*Results in*
.. raw:: html
Orbital weighted band structure for a chain of s-p orbitals in 1D chain
Why use PySKTB ❔
------------------------------
- Specifically designed for Slater-Koster tight binding calculations, which means that it includes all of the necessary tools and functions for constructing and solving these types of models.
- Written in Python, which is a high-level programming language that is easy to read and write. This can make it particularly useful for prototyping and developing code quickly.
- Open source, which means that it is freely available to use and modify. This can be useful for researchers who want to modify the code to suit their specific needs or who want to contribute to the development of the package.
- Provides a variety of functions for constructing and solving tight binding models, including functions for generating the tight binding Hamiltonian matrix, diagonalizing the matrix to obtain the energy eigenvalues and eigenvectors, and calculating various properties of the resulting electronic structure.
- Includes tools for visualizing the results of the calculations, such as functions for plotting the band structure, density of states, and wave functions.
- Well-documented, with detailed instructions and examples provided in the package documentation. This can make it easier to get started with the package and to understand how to use its various features.
- Actively maintained and developed, which means that it is likely to receive updates and new features over time.
.. _features:
✨ Features
--------
- Generate s,p,d interactions in any given lattice
- Total energy *for insulators and semimetals*
- Specify range of interaction with more then Nearest neibghor
- Spin Polarized calculations
- Spin orbit coupling *(only for p orbitals as of now)*
- Plot orbital weighted colorplots
- Integration with `pymatgen `_ structres
- JIT optimized with numba
- Parallelization on kpoints
.. _installation:
📦 Installation
---------------------
.. code-block:: bash
pip install pysktb
:mod:`pysktb`'s primitives
--------------------------
.. automodule:: pysktb
:no-members:
:no-inherited-members:
.. currentmodule:: pysktb
.. autosummary::
:template: class.rst
pysktb.Atom
pysktb.Lattice
pysktb.Structure
pysktb.Hamiltonian
pysktb.System
.. toctree::
:maxdepth: 1
:caption: Overview:
Home
Installation
What are Tight Binding models?
.. toctree::
:maxdepth: 2
:caption: Usage Examples:
examples/examples
.. toctree::
:maxdepth: 1
:caption: API reference:
Atom
Lattice
Structure
Hamiltonian
System
