Graph state extraction from two-dimensional cluster states

Abstract We propose schemes to extract arbitrary graph states from two-dimensional cluster states by locally manipulating the qubits solely via single-qubit measurements. We introduce graph state manipulation tools that allow one to increase the local vertex degree and to merge subgraphs. We utilize these tools together with the previously introduced zipper scheme that generates multiple edges between distant vertices to extract the desired graph state from a two-dimensional cluster state. We show how to minimize overheads by avoiding multiple edges, and compare with a local manipulation strategy based on measurement-based quantum computation together with transport. These schemes have direct applications in entanglement-based quantum networks, sensor networks, and distributed quantum computing in general.

Authors

Publication Details

Journal
New Journal of Physics
Published
2025-09-01
DOI
https://doi.org/10.1088/1367-2630/ae02bd
Citations
1
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
2.48

Funders

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article

Graph state extraction from two-dimensional cluster states

Lina Vandré, Alexander Pirker, Wolfgang Dür, Julia Freund
1 citations
New Journal of Physics
Neural Networks and Applications
2.48
article

Graph state extraction from two-dimensional cluster states

Lina Vandré, Alexander Pirker, Wolfgang Dür, Julia Freund
article en
1 citations

Abstract

Abstract We propose schemes to extract arbitrary graph states from two-dimensional cluster states by locally manipulating the qubits solely via single-qubit measurements. We introduce graph state manipulation tools that allow one to increase the local vertex degree and to merge subgraphs. We utilize these tools together with the previously introduced zipper scheme that generates multiple edges between distant vertices to extract the desired graph state from a two-dimensional cluster state. We show how to minimize overheads by avoiding multiple edges, and compare with a local manipulation strategy based on measurement-based quantum computation together with transport. These schemes have direct applications in entanglement-based quantum networks, sensor networks, and distributed quantum computing in general.

New Journal of PhysicsVol. 27(9)
Deutsche Forschungsgemeinschaft, Austrian Science Fund, Chinesisch-Deutsche Zentrum für Wissenschaftsförderung, Stiftung der Deutschen Wirtschaft
Openalex Percentile: Top 9%
Neural Networks and Applications
2.48
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