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This research presents a breakthrough in simulating GHZ-state distillation circuits, reducing computational complexity from exponential to constant time $O(1)$. By enabling the discovery of highly efficient entanglement purification protocols, this method directly accelerates the development of scalable quantum networks and error-corrected quantum processors. The work establishes a new benchmark for optimizing multipartite entanglement resources under arbitrary noise models.
Source coveringarXiv
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GHZ-Preserving Gates and Optimized Distillation Circuits

arXiv2 min read

arXiv:2510.25854v2 Announce Type: replace Abstract: Greenberger-Horne-Zeilinger (GHZ) states play a central role in quantum computing and communication protocols, as a typical multipartite entanglement resource. This work introduces an efficient enumeration and simulation method for circuits that preserve and distill noisy GHZ states, significantly reducing the simulation complexity of a gate on $n$ qubits, from exponential $O(2^n)$ for standard state-vector methods or $O(n)$ for Clifford circuits, to a constant $O(1)$ for the method presented here. This method has profound implications for the design of quantum networks, where preservation and purification of entanglement with minimal resource overhead is critical. In particular, we demonstrate the use of the new method in an optimization procedure enabled by the fast simulation, that discovers GHZ distillation circuits far outperforming the state of the art. Fine-tuning to arbitrary noise models is possible as well. We also show that the method naturally extends to graph states that are local Clifford equivalent to GHZ states.

Abstract:Greenberger-Horne-Zeilinger (GHZ) states play a central role in quantum computing and communication protocols, as a typical multipartite entanglement resource. This work introduces an efficient enumeration and simulation method for circuits that preserve and distill noisy GHZ states, significantly reducing the simulation complexity of a gate on $n$ qubits, from exponential $O(2^n)$ for standard state-vector methods or $O(n)$ for Clifford circuits, to a constant $O(1)$ for the method presented here. This method has profound implications for the design of quantum networks, where preservation and purification of entanglement with minimal resource overhead is critical. In particular, we demonstrate the use of the new method in an optimization procedure enabled by the fast simulation, that discovers GHZ distillation circuits far outperforming the state of the art. Fine-tuning to arbitrary noise models is possible as well. We also show that the method naturally extends to graph states that are local Clifford equivalent to GHZ states.

22 pages, 7 figures, code link https://doi.org/10.5281/zenodo.17470505

arXiv:2510.25854 [quant-ph]

(or arXiv:2510.25854v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2510.25854 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 247 words

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