Graph-theoretical optimization of fusion-based graph state generation
Project description
OptGraphState
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.
Tutorials: https://github.com/seokhyung-lee/OptGraphState/raw/main/tutorials.pdf
API reference: https://seokhyung-lee.github.io/OptGraphState
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