LTB-Symm


NameLTB-Symm JSON
Version 1.0.0 PyPI version JSON
download
home_pagehttps://github.com/khsrali/LTB-Symm
SummaryLarge Scale Tight Binding + Symmetries
upload_time2023-05-09 23:07:17
maintainer
docs_urlNone
authorAli Khosravi, Andrea Silva
requires_python>=3.7
licenseGNU under General Public License v3.0
keywords tight-binding wave-function symmetries
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            <img
src="https://github.com/khsrali/LTB-Symm/blob/develop/docs/source/_images/logo_V_0.1.png?raw=true"
width="1200" alt="image" />


# LTB-Symm

LTB-Symm is a publicly available code that does two things: **large
scale tight-binding** (LTB) calculation of 2D materials, and checks
**topological symmetries** (Symm) of their wave functions.

## Who benefits

LTB-Symm is an ideal choice for researchers looking for a ready-to-use,
easy-to-modify, and MPI-implemented TB code for large scale 2D
structures. Up to 1 (0.1) Milions atoms for limited (vast) K-points, is
(easily) managable.

Specially communities who deal with twisted bilayer/multilayer graphene.

All input needed are:  
1.  Coordinate of atoms/orbitals, e.g. lammpstrj, XYZ
2.  Functional form of Hamiltoninan

And possible outputs are:  
-   Bands structure,
-   Density of States,
-   Check topological symmetries of wave functions.
-   Shape of the wavefunction

## Bold features

-   MPI implemented, able to run on HPC clusters.
-   Object Oriented, easy to modify for multi purpose.
-   Efficient, calculate only a few energy levels that are needed.
-   Ideal for 2D materials, e.g. graphene.
-   Many routings are automated.
-   The only open-source code that we know of which is able to investigate group symmetries in this way.
            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/khsrali/LTB-Symm",
    "name": "LTB-Symm",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.7",
    "maintainer_email": "",
    "keywords": "tight-binding wave-function symmetries",
    "author": "Ali Khosravi, Andrea Silva",
    "author_email": "khsrali@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/e3/e5/17fc3b986659f7dbd185d822514eacedbc83450b2b32a78f5d1b3a6f0907/LTB-Symm-1.0.0.tar.gz",
    "platform": null,
    "description": "<img\nsrc=\"https://github.com/khsrali/LTB-Symm/blob/develop/docs/source/_images/logo_V_0.1.png?raw=true\"\nwidth=\"1200\" alt=\"image\" />\n\n\n# LTB-Symm\n\nLTB-Symm is a publicly available code that does two things: **large\nscale tight-binding** (LTB) calculation of 2D materials, and checks\n**topological symmetries** (Symm) of their wave functions.\n\n## Who benefits\n\nLTB-Symm is an ideal choice for researchers looking for a ready-to-use,\neasy-to-modify, and MPI-implemented TB code for large scale 2D\nstructures. Up to 1 (0.1) Milions atoms for limited (vast) K-points, is\n(easily) managable.\n\nSpecially communities who deal with twisted bilayer/multilayer graphene.\n\nAll input needed are:  \n1.  Coordinate of atoms/orbitals, e.g. lammpstrj, XYZ\n2.  Functional form of Hamiltoninan\n\nAnd possible outputs are:  \n-   Bands structure,\n-   Density of States,\n-   Check topological symmetries of wave functions.\n-   Shape of the wavefunction\n\n## Bold features\n\n-   MPI implemented, able to run on HPC clusters.\n-   Object Oriented, easy to modify for multi purpose.\n-   Efficient, calculate only a few energy levels that are needed.\n-   Ideal for 2D materials, e.g. graphene.\n-   Many routings are automated.\n-   The only open-source code that we know of which is able to investigate group symmetries in this way.",
    "bugtrack_url": null,
    "license": "GNU under General Public License v3.0",
    "summary": "Large Scale Tight Binding + Symmetries",
    "version": "1.0.0",
    "project_urls": {
        "Homepage": "https://github.com/khsrali/LTB-Symm"
    },
    "split_keywords": [
        "tight-binding",
        "wave-function",
        "symmetries"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "e3e517fc3b986659f7dbd185d822514eacedbc83450b2b32a78f5d1b3a6f0907",
                "md5": "c4f14088d7f5c934ec0635fe6d17c214",
                "sha256": "da8ae413e3fc342c432d315f401cc36ecd25a1f0366443dcd28c6dda675837bc"
            },
            "downloads": -1,
            "filename": "LTB-Symm-1.0.0.tar.gz",
            "has_sig": false,
            "md5_digest": "c4f14088d7f5c934ec0635fe6d17c214",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.7",
            "size": 24370,
            "upload_time": "2023-05-09T23:07:17",
            "upload_time_iso_8601": "2023-05-09T23:07:17.204395Z",
            "url": "https://files.pythonhosted.org/packages/e3/e5/17fc3b986659f7dbd185d822514eacedbc83450b2b32a78f5d1b3a6f0907/LTB-Symm-1.0.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-05-09 23:07:17",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "khsrali",
    "github_project": "LTB-Symm",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "ltb-symm"
}
        
Elapsed time: 1.40574s