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Python package

sbovqaopt: Surrogate-based optimizer for variational quantum algorithms

The sbovqaopt package provides a surrogate-based optimizer for variational quantum algorithms as introduced in arXiv:2204.05451.

Installation

The sbovqaopt package distribution is hosted on PyPI and can be installed via pip:

pip install sbovqaopt

Usage

For examples of using sbovqaopt, see the example notebooks and unit tests.

Development

For development purposes, the package and its requirements can be installed by cloning the repository locally:

git clone https://github.com/sandialabs/sbovqaopt
cd sbovqaopt
pip install -r requirements.txt
pip install -e .

Citation

If you use or refer to this project in any publication, please cite the corresponding paper:

Ryan Shaffer, Lucas Kocia, Mohan Sarovar. Surrogate-based optimization for variational quantum algorithms. arXiv:2204.05451 (2022).

Release files for sbovqaopt 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sbovqaopt 0.1.0
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Built distribution (wheel)

Table of built distributions (wheels) for sbovqaopt 0.1.0
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sbovqaopt-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 12.7 kB

Release files / sbovqaopt-0.1.0.tar.gz

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0.1.0 This release

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