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Graph-theoretical optimization of fusion-based graph state generation

Project description

OptGraphState

Version 0.1.1

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. 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.
  • 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.

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