| Name | pybinding-dev JSON |
| Version |
1.0.5
JSON |
| download |
| home_page | None |
| Summary | Package for tight-binding calculations, Documentation: http://pybinding.site/ (c) 2015-2024 |
| upload_time | 2024-10-16 11:30:39 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | Copyright (c) 2015 - 2017, Dean Moldovan All rights reserved. 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. 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. |
| keywords |
pybinding
tight-binding
solid-state physics
physics
cmt
quantum
graphene
tmd
kpm
cpgf
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<img src="/docs/pb.png?raw=true" alt="pybinding" width=220px/>
[](https://zenodo.org/badge/latestdoi/20541/dean0x7d/pybinding)
[](license.md)
[](https://gitter.im/dean0x7d/pybinding)
[](http://docs.pybinding.site/)
[](https://travis-ci.org/dean0x7d/pybinding)
[](https://ci.appveyor.com/project/dean0x7d/pybinding)
Pybinding is a Python package for numerical tight-binding calculations in solid state physics.
The main features include:
* **Declarative model construction** - The user just needs to describe *what* the model should be,
but not *how* to build it. Pybinding will take care of the numerical details of building the
Hamiltonian matrix so users can concentrate on the physics, i.e. the quantum properties of the
model.
* **Fast compute** - Pybinding's implementation of the kernel polynomial method allows for very
fast calculation of various physical properties of tight-binding systems. Exact diagonalization
is also available through the use of scipy's eigenvalue solvers. The framework is very flexible
and allows the addition of user-defined computation routines.
* **Result analysis and visualization** - The package contains utility functions for post-processing
the raw result data. The included plotting functions are tailored for tight-binding problems to
help visualize the model structure and to make sense of the results.
The code interface is written in Python with the aim to be as user-friendly and flexible as
possible. Under the hood, C++17 is used to accelerate demanding tasks to deliver high performance
with low memory usage.
See the [documentation] for more details.
## Install
Pybinding can be installed on Windows, Linux or Mac, with the following prerequisites:
* [Python] 3.9 or newer (Python 2.x is not supported)
* The [SciPy] stack of scientific packages, with required versions:
* numpy >= v1.12
* scipy >= v0.19
* matplotlib >= v2.0
* If you're using Linux, you'll also need GCC >= v5.0 (or clang >= v3.5) and CMake >= v3.5.
Detailed [install instructions] are part of the documentation, but if you already have all the
prerequisites, it's just a simple case of using `pip`, Python's usual package manager:
pip install pybinding
## Features
The goal of the project is to develop a tight-binding code framework which is fast, flexible and
easy to use. This is just a quick overview of some of the features. See the [documentation] for
more details and a guide to get started.
* Construction of arbitrary tight-binding lattices and geometries: 1 to 3 dimensions
(including multilayer 2D systems), periodic or finite size (with fine control of edges)
* Easy polygon shape definition for 2D systems and freeform shapes for n-dimensional systems
* Geometric deformations and defects: defined via displacement and state functions
* Fields and arbitrary effects: defined via hopping and onsite energy functions
* Kernel polynomial method: a fast way to compute Green's function, spectral densities of
arbitrary operators, electrical conductivity, or various other user-defined KPM methods
* Exact diagonalization: standard dense and sparse eigenvalues solvers (always available)
and the [FEAST] solver (only available when compiled with Intel's MKL)
* Transport: scattering systems with semi-infinite leads can be constructed in pybinding and then
solved using the [Kwant compatibility] layer
* Model and result objects have builtin plotting functions for easy visualization
## Benchmarks
One of the main features of pybinding is an easy-to-use and fast model builder. This can be a
demanding task for large or complicated systems. Great care was taken to make this process fast.
The following figures compare the performance of pybinding with the [Kwant] package. They present
the time and memory required to build a Hamiltonian matrix which describes a tight-binding system.
Pybinding features good performance and a low memory footprint by using contiguous data structures
and vectorized operations.
<p align="center">
<img src="/docs/benchmarks/system_build.png?raw=true" alt="Tight-binding model build benchmark"/>
</p>
See the [benchmarks] section of the documentation for details on the testbed hardware and software,
as well as the source code which can be used to reproduce the results.
## Citing
Pybinding is free to use under the simple conditions of the [BSD open source license](license.md).
If you wish to use results produced with this package in a scientific publication, please just
mention the package name in the text and cite the Zenodo DOI of this project:
[](https://zenodo.org/badge/latestdoi/20541/dean0x7d/pybinding)
You'll find a *"Cite as"* section in the bottom right of the Zenodo page. You can select a citation
style from the dropdown menu or export the data in BibTeX and similar formats.
## Questions?
If you have any questions, feel free to join the [chat room on Gitter].
You can also open an issue at the [tracker].
[documentation]: http://docs.pybinding.site/
[install instructions]: http://docs.pybinding.site/page/install/index.html
[Python]: https://www.python.org/
[SciPy]: http://www.scipy.org/
[FEAST]: http://www.ecs.umass.edu/~polizzi/feast/index.htm
[Kwant compatibility]: http://docs.pybinding.site/page/advanced/kwant.html
[Kwant]: http://kwant-project.org/
[benchmarks]: http://docs.pybinding.site/page/benchmarks/index.html
[chat room on Gitter]: https://gitter.im/dean0x7d/pybinding
[tracker]: https://github.com/dean0x7d/pybinding/issues
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Exact diagonalization\n is also available through the use of scipy's eigenvalue solvers. The framework is very flexible\n and allows the addition of user-defined computation routines.\n\n* **Result analysis and visualization** - The package contains utility functions for post-processing\n the raw result data. The included plotting functions are tailored for tight-binding problems to\n help visualize the model structure and to make sense of the results.\n\nThe code interface is written in Python with the aim to be as user-friendly and flexible as\npossible. Under the hood, C++17 is used to accelerate demanding tasks to deliver high performance\nwith low memory usage.\n\nSee the [documentation] for more details.\n\n## Install\n\nPybinding can be installed on Windows, Linux or Mac, with the following prerequisites:\n\n* [Python] 3.9 or newer (Python 2.x is not supported)\n* The [SciPy] stack of scientific packages, with required versions:\n * numpy >= v1.12\n * scipy >= v0.19\n * matplotlib >= v2.0\n* If you're using Linux, you'll also need GCC >= v5.0 (or clang >= v3.5) and CMake >= v3.5.\n\nDetailed [install instructions] are part of the documentation, but if you already have all the\nprerequisites, it's just a simple case of using `pip`, Python's usual package manager:\n\n pip install pybinding\n\n\n## Features\n\nThe goal of the project is to develop a tight-binding code framework which is fast, flexible and\neasy to use. This is just a quick overview of some of the features. 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