TB2J


NameTB2J JSON
Version 0.9.12.10 PyPI version JSON
download
home_pageNone
SummaryTB2J: First principle to Heisenberg exchange J using tight-binding Green function method
upload_time2025-08-19 21:04:02
maintainerNone
docs_urlNone
authorNone
requires_python>=3.6
licenseBSD-2-Clause
keywords magnetism dft heisenberg exchange physics
VCS
bugtrack_url
requirements wheel numpy scipy matplotlib ase tqdm pathos packaging sympair sisl pre-commit
Travis-CI
coveralls test coverage No coveralls.
            [![Python application](https://github.com/mailhexu/TB2J/actions/workflows/python-app.yml/badge.svg)](https://github.com/mailhexu/TB2J/actions/workflows/python-app.yml)
[![Documentation Status](https://readthedocs.org/projects/tb2j/badge/?version=latest)](https://tb2j.readthedocs.io/en/latest/?badge=latest)
[![Build Status](https://app.travis-ci.com/mailhexu/TB2J.svg?branch=master)](https://app.travis-ci.com/mailhexu/TB2J)
[![Downloads](https://pepy.tech/badge/tb2j)](https://pepy.tech/project/tb2j)

## Description

TB2J is a open source python package for calculating the magnetic interaction parameters in Heisenberg models from DFT. It use the magnetic force theorem and take the local rigid spin rotation as a perturbation in the Green's function method. 

The TB2J project is initialized in the PhyTheMa and Nanomat teams in the University of Liege.

The features include:
 - Calculates  parameters in Heisenberg model, including isotropic exchange, anisotropic exchange, Dyzanoshinskii-Moriya interaction.
 - Can use the input from many DFT codes with Wannier90, e.g. Abinit, Quantum Espresso, Siesta, VASP, etc.
 - Can use input from DFT codes with numerical orbitals from Siesta, OpenMX and ABACUS.
 - Calculate magnon band structure from the Heisenberg Hamiltonian.
 - Generate input for spin dynamics/Monte Carlo codes MULTIBINIT.
 - Require only ground state DFT calculation.
 - No need for supercells.
 - Calculate magnetic interaction up to large distance. 
 - Minimal user input, which allows for a black-box like experience and automatic workflows.
 - Versatile API on both the input (DFT Hamiltonian) and the output (Heisenberg model) sides.

For more information, see the documentation on
 <https://tb2j.readthedocs.io/en/latest/>

## Dependencies
* python (tested for ver 3.6)
* numpy 
* scipy
* ASE (atomic simulation environment) 
* matplotlib  (optional) if you want to plot magnon band structure directly. 
* sisl (optional) for Siesta interface

## Installation
pip install TB2J

## Message:
- We welcome contributions. If you would like to add the interface to other codes, or extend the capability of TB2J, please contact us! <mailhexu_AT_gmail_DOT_com>


            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "TB2J",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.6",
    "maintainer_email": "Xu He <mailhexu@gmail.com>",
    "keywords": "magnetism, DFT, Heisenberg, exchange, physics",
    "author": null,
    "author_email": "Xu He <mailhexu@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/ee/13/b9a091df1da4b7beb5b28b3f1b33767fea76b7b2dcebeddfed838ca39367/tb2j-0.9.12.10.tar.gz",
    "platform": null,
    "description": "[![Python application](https://github.com/mailhexu/TB2J/actions/workflows/python-app.yml/badge.svg)](https://github.com/mailhexu/TB2J/actions/workflows/python-app.yml)\n[![Documentation Status](https://readthedocs.org/projects/tb2j/badge/?version=latest)](https://tb2j.readthedocs.io/en/latest/?badge=latest)\n[![Build Status](https://app.travis-ci.com/mailhexu/TB2J.svg?branch=master)](https://app.travis-ci.com/mailhexu/TB2J)\n[![Downloads](https://pepy.tech/badge/tb2j)](https://pepy.tech/project/tb2j)\n\n## Description\n\nTB2J is a open source python package for calculating the magnetic interaction parameters in Heisenberg models from DFT. It use the magnetic force theorem and take the local rigid spin rotation as a perturbation in the Green's function method. \n\nThe TB2J project is initialized in the PhyTheMa and Nanomat teams in the University of Liege.\n\nThe features include:\n - Calculates  parameters in Heisenberg model, including isotropic exchange, anisotropic exchange, Dyzanoshinskii-Moriya interaction.\n - Can use the input from many DFT codes with Wannier90, e.g. Abinit, Quantum Espresso, Siesta, VASP, etc.\n - Can use input from DFT codes with numerical orbitals from Siesta, OpenMX and ABACUS.\n - Calculate magnon band structure from the Heisenberg Hamiltonian.\n - Generate input for spin dynamics/Monte Carlo codes MULTIBINIT.\n - Require only ground state DFT calculation.\n - No need for supercells.\n - Calculate magnetic interaction up to large distance. \n - Minimal user input, which allows for a black-box like experience and automatic workflows.\n - Versatile API on both the input (DFT Hamiltonian) and the output (Heisenberg model) sides.\n\nFor more information, see the documentation on\n <https://tb2j.readthedocs.io/en/latest/>\n\n## Dependencies\n* python (tested for ver 3.6)\n* numpy \n* scipy\n* ASE (atomic simulation environment) \n* matplotlib  (optional) if you want to plot magnon band structure directly. \n* sisl (optional) for Siesta interface\n\n## Installation\npip install TB2J\n\n## Message:\n- We welcome contributions. If you would like to add the interface to other codes, or extend the capability of TB2J, please contact us! <mailhexu_AT_gmail_DOT_com>\n\n",
    "bugtrack_url": null,
    "license": "BSD-2-Clause",
    "summary": "TB2J: First principle to Heisenberg exchange J using tight-binding Green function method",
    "version": "0.9.12.10",
    "project_urls": {
        "Documentation": "https://tb2j.readthedocs.io/en/latest/",
        "Homepage": "https://github.com/mailhexu/TB2J",
        "Issues": "https://github.com/mailhexu/TB2J/issues",
        "Repository": "https://github.com/mailhexu/TB2J"
    },
    "split_keywords": [
        "magnetism",
        " dft",
        " heisenberg",
        " exchange",
        " physics"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "5e70a79599ba48fad9ebc4bd932c341e512015cd365fbf5e83008068f4130fdb",
                "md5": "32191fbe97a208234a46462f40fb03ec",
                "sha256": "d8715d34a68804fe628b40c0200d54a1d9f702db7b63b23e881555f63dd4f591"
            },
            "downloads": -1,
            "filename": "tb2j-0.9.12.10-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "32191fbe97a208234a46462f40fb03ec",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.6",
            "size": 199058,
            "upload_time": "2025-08-19T21:04:01",
            "upload_time_iso_8601": "2025-08-19T21:04:01.261497Z",
            "url": "https://files.pythonhosted.org/packages/5e/70/a79599ba48fad9ebc4bd932c341e512015cd365fbf5e83008068f4130fdb/tb2j-0.9.12.10-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "ee13b9a091df1da4b7beb5b28b3f1b33767fea76b7b2dcebeddfed838ca39367",
                "md5": "5de788c711e2e2ed1292894c665286c4",
                "sha256": "9775f10df9c2898982b9cf9a67b5069b980a230190404a409aefb1873bbf94c7"
            },
            "downloads": -1,
            "filename": "tb2j-0.9.12.10.tar.gz",
            "has_sig": false,
            "md5_digest": "5de788c711e2e2ed1292894c665286c4",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.6",
            "size": 161818,
            "upload_time": "2025-08-19T21:04:02",
            "upload_time_iso_8601": "2025-08-19T21:04:02.770015Z",
            "url": "https://files.pythonhosted.org/packages/ee/13/b9a091df1da4b7beb5b28b3f1b33767fea76b7b2dcebeddfed838ca39367/tb2j-0.9.12.10.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-08-19 21:04:02",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "mailhexu",
    "github_project": "TB2J",
    "travis_ci": true,
    "coveralls": false,
    "github_actions": true,
    "requirements": [
        {
            "name": "wheel",
            "specs": []
        },
        {
            "name": "numpy",
            "specs": [
                [
                    ">",
                    "1.16.5"
                ]
            ]
        },
        {
            "name": "scipy",
            "specs": []
        },
        {
            "name": "matplotlib",
            "specs": []
        },
        {
            "name": "ase",
            "specs": [
                [
                    ">=",
                    "3.19"
                ]
            ]
        },
        {
            "name": "tqdm",
            "specs": [
                [
                    ">=",
                    "4.42.0"
                ]
            ]
        },
        {
            "name": "pathos",
            "specs": []
        },
        {
            "name": "packaging",
            "specs": [
                [
                    ">=",
                    "20.0"
                ]
            ]
        },
        {
            "name": "sympair",
            "specs": [
                [
                    ">=",
                    "0.1.0"
                ]
            ]
        },
        {
            "name": "sisl",
            "specs": [
                [
                    ">=",
                    "0.9.0"
                ]
            ]
        },
        {
            "name": "pre-commit",
            "specs": []
        }
    ],
    "lcname": "tb2j"
}
        
Elapsed time: 0.92377s