1Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
2Centre for Engineered Quantum Systems, School of Physics, University of Sydney, Sydney, NSW 2006, Australia
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Abstract
Graph states are versatile resources for various quantum information processing tasks, including measurement-based quantum computing and quantum repeaters. Although the type-II fusion gate enables all-optical generation of graph states by combining small graph states, its non-deterministic nature hinders the efficient generation of large graph states. In this work, we present a graph-theoretical strategy to effectively optimize fusion-based generation of any given graph state, along with a Python package OptGraphState. Our strategy comprises three stages: simplifying the target graph state, building a fusion network, and determining the order of fusions. Utilizing this proposed method, we evaluate the resource overheads of random graphs and various well-known graphs. Additionally, we investigate the success probability of graph state generation given a restricted number of available resource states. We expect that our strategy and software will assist researchers in developing and assessing experimentally viable schemes that use photonic graph states.
Featured image: Example of an unraveled graph and its corresponding fusion network, derived from the original graph state using our proposed strategy. The unraveled graph, a simplified variant of the original, yields the same graph state following the application of specific local Clifford gates and type-II fusions. The fusion network represents a systematic arrangement of basic resource states, which instructs the necessary fusions to reconstruct the original graph state.
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Cited by
[1] Brendan Pankovich, Alex Neville, Angus Kan, Srikrishna Omkar, Kwok Ho Wan, and Kamil Brádler, “Flexible entangled state generation in linear optics”, arXiv:2310.06832, (2023).
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