pennylane-quantuminspire


Namepennylane-quantuminspire JSON
Version 0.6.0 PyPI version JSON
download
home_pagehttps://www.quantum-inspire.com
SummaryThe PennyLane-QuantumInspire plugin integrates the Quantum Inspire quantum computing backends with PennyLane's quantum machine learning capabilities.
upload_time2025-02-11 09:52:27
maintainerNone
docs_urlNone
authorQuantum Inspire
requires_python<4.0,>=3.9
licenseNone
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # PennyLane-QuantumInspire Plugin

[![License](https://img.shields.io/github/license/qutech-delft/qiskit-quantuminspire.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)

**[PennyLane]** is an open-source SDK for quantum programming.
This project contains a provider that allows access to **[Quantum Inspire]** quantum systems.

## Getting started

All information needed to get started using this plugin can be found in our [documentation](https://qutech-delft.github.io/pennylane-quantuminspire/). Some particularly useful links:

1. [Installation and login](https://qutech-delft.github.io/pennylane-quantuminspire/getting_started/installation.html)
2. [Submitting your first circuit](https://qutech-delft.github.io/pennylane-quantuminspire/getting_started/submitting.html)
3. [Example notebooks](https://qutech-delft.github.io/pennylane-quantuminspire/notebooks/index.html)

[quantum inspire]: https://www.quantum-inspire.com/
[pennylane]: https://pennylane.ai/


            

Raw data

            {
    "_id": null,
    "home_page": "https://www.quantum-inspire.com",
    "name": "pennylane-quantuminspire",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "<4.0,>=3.9",
    "maintainer_email": null,
    "keywords": null,
    "author": "Quantum Inspire",
    "author_email": "support@quantum-inspire.com",
    "download_url": "https://files.pythonhosted.org/packages/61/cf/80e4546ea1c074f46272db8bc0ccceded8c0c1c3b61da3203524bbe6ea3f/pennylane_quantuminspire-0.6.0.tar.gz",
    "platform": null,
    "description": "# PennyLane-QuantumInspire Plugin\n\n[![License](https://img.shields.io/github/license/qutech-delft/qiskit-quantuminspire.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)\n\n**[PennyLane]** is an open-source SDK for quantum programming.\nThis project contains a provider that allows access to **[Quantum Inspire]** quantum systems.\n\n## Getting started\n\nAll information needed to get started using this plugin can be found in our [documentation](https://qutech-delft.github.io/pennylane-quantuminspire/). Some particularly useful links:\n\n1. [Installation and login](https://qutech-delft.github.io/pennylane-quantuminspire/getting_started/installation.html)\n2. [Submitting your first circuit](https://qutech-delft.github.io/pennylane-quantuminspire/getting_started/submitting.html)\n3. [Example notebooks](https://qutech-delft.github.io/pennylane-quantuminspire/notebooks/index.html)\n\n[quantum inspire]: https://www.quantum-inspire.com/\n[pennylane]: https://pennylane.ai/\n\n",
    "bugtrack_url": null,
    "license": null,
    "summary": "The PennyLane-QuantumInspire plugin integrates the Quantum Inspire quantum computing backends with PennyLane's quantum machine learning capabilities.",
    "version": "0.6.0",
    "project_urls": {
        "Documentation": "https://qutech-delft.github.io/pennylane-quantuminspire/",
        "Homepage": "https://www.quantum-inspire.com",
        "Repository": "https://github.com/qutech-delft/pennylane-quantuminspire"
    },
    "split_keywords": [],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "24a5d54c65bfbe4cf70ea65bb52b2dab593a2dc3ad5f4265530ad8b30e873f86",
                "md5": "2a7ce078ae465c3f15a6e10ec72100d9",
                "sha256": "27e7a00924660dcd37308cd55d213f4deadf3d9491bed5aaf8fb7a2e452517a3"
            },
            "downloads": -1,
            "filename": "pennylane_quantuminspire-0.6.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "2a7ce078ae465c3f15a6e10ec72100d9",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "<4.0,>=3.9",
            "size": 7149,
            "upload_time": "2025-02-11T09:52:26",
            "upload_time_iso_8601": "2025-02-11T09:52:26.084081Z",
            "url": "https://files.pythonhosted.org/packages/24/a5/d54c65bfbe4cf70ea65bb52b2dab593a2dc3ad5f4265530ad8b30e873f86/pennylane_quantuminspire-0.6.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "61cf80e4546ea1c074f46272db8bc0ccceded8c0c1c3b61da3203524bbe6ea3f",
                "md5": "d0c698b9bcd17bfe4566961e36277142",
                "sha256": "fb7a9b6d733e9b442e0f68435da39a0ad39fa2e070ec87e8253425a314c27352"
            },
            "downloads": -1,
            "filename": "pennylane_quantuminspire-0.6.0.tar.gz",
            "has_sig": false,
            "md5_digest": "d0c698b9bcd17bfe4566961e36277142",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "<4.0,>=3.9",
            "size": 6954,
            "upload_time": "2025-02-11T09:52:27",
            "upload_time_iso_8601": "2025-02-11T09:52:27.919624Z",
            "url": "https://files.pythonhosted.org/packages/61/cf/80e4546ea1c074f46272db8bc0ccceded8c0c1c3b61da3203524bbe6ea3f/pennylane_quantuminspire-0.6.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-02-11 09:52:27",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "qutech-delft",
    "github_project": "pennylane-quantuminspire",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "tox": true,
    "lcname": "pennylane-quantuminspire"
}
        
Elapsed time: 0.48323s