https://github.com/sandialabs/sbovqaopt
Surrogate-based optimizer for variational quantum algorithms.
https://github.com/sandialabs/sbovqaopt
scr-2807 snl-quantum-computing
Last synced: 7 months ago
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Surrogate-based optimizer for variational quantum algorithms.
- Host: GitHub
- URL: https://github.com/sandialabs/sbovqaopt
- Owner: sandialabs
- License: other
- Created: 2022-07-22T20:56:56.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-04-04T20:41:27.000Z (about 3 years ago)
- Last Synced: 2025-01-11T15:24:11.267Z (over 1 year ago)
- Topics: scr-2807, snl-quantum-computing
- Language: Python
- Homepage:
- Size: 37.1 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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# sbovqaopt: Surrogate-based optimizer for variational quantum algorithms
The `sbovqaopt` package provides a surrogate-based optimizer for variational quantum algorithms as introduced in
[Phys. Rev. A 107, 032415](https://doi.org/10.1103/PhysRevA.107.032415),
[arXiv:2204.05451](https://arxiv.org/abs/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](./examples) and [unit tests](./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._ Phys. Rev. A 107, 032415 (2023). https://doi.org/10.1103/PhysRevA.107.032415