Graph-theoretical optimization of fusion-based graph state generation
Project description
OptGraphState
Version 0.3.1
Graph-theoretical optimization of fusion-based graph state generation.
OptGraphState is a python package that implements the graph-theoretical strategy to optimize the fusion-based generation of any graph state, which is proposed in Lee & Jeong, arXiv:2304.11988 [quant-ph] (2023).
The package has the following features:
- Finding a resource-efficient method of generating a given graph state through type-II fusions from multiple basic resource states, which are three-qubit linear graph states.
- Computing the corresponding resource overhead, which is quantified by the average number of required basic resource states or fusion attempts.
- Computing the success probability of graph state generation when the number of provided basic resource states is limited.
- Visualizing the original graph (of the graph state you want to generate), unraveled graphs, and fusion networks. An unraveled graph is a simplified graph where the corresponding graph state is equivalent to the desired graph state up to fusions and single-qubit Clifford operations. A fusion network is a graph that instructs the fusions between basic resource states required to generate the desired graph state.
- Various predefined sample graphs for input.
Installation
pip install optgraphstate
Manuals
Tutorials: https://github.com/seokhyung-lee/OptGraphState/raw/main/tutorials.pdf
API reference: https://seokhyung-lee.github.io/OptGraphState
License
OptGraphState is distributed under the MIT license. Please see the LICENSE file for more details.
Citation
If you want to cite OptGraphState in an academic work, please cite the arXiv preprint:
@misc{lee2023graph,
title={Graph-theoretical optimization of fusion-based graph state generation},
author={Seok-Hyung Lee and Hyunseok Jeong},
year={2023},
eprint={2304.11988},
archivePrefix={arXiv},
primaryClass={quant-ph},
url={https://arxiv.org/abs/2304.11988}
}
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file optgraphstate-0.3.1.tar.gz
.
File metadata
- Download URL: optgraphstate-0.3.1.tar.gz
- Upload date:
- Size: 26.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b6379c1e00aa7f301017eb677e605a66d46c6204edada0717015c53b8bb775f2 |
|
MD5 | 8e764932022d911f2283889c1e7e6325 |
|
BLAKE2b-256 | abbf4cac63a5702967a9f7e95bb5952cc238b51b9a483d809c46069c017a53ea |
File details
Details for the file optgraphstate-0.3.1-py3-none-any.whl
.
File metadata
- Download URL: optgraphstate-0.3.1-py3-none-any.whl
- Upload date:
- Size: 27.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d2a854a8e7064ec19b5599747ccfd1bad804dfaf4bfe6c3f8298cec47d320aba |
|
MD5 | cbe0e6cd33130ab862e3d446ea34f1b3 |
|
BLAKE2b-256 | 559910242cb48f9bd4b10c8c50ec737eb43b01eef4e8a9879fddc10a6d03e2b3 |