Robust Entanglement Witnessing via Dense Network Coding with Graph States
Abstract
Practical tests for witnessing entanglement in the presence of noise are needed to verify and apply entanglement-based applications in real-world communication networks. Quantum dense network coding is a communication protocol that uses an entangled state preparation together with quantum communication to halve the amount of communication needed to evaluate certain bijective functions in networks having multiple senders and one receiver. In this work, we consider a dense network coding protocol that uses graph state entanglement to implement a family of affine transformations, we derive a bound on the success probability that can be achieved by classical networks, and we show that the noise robustness exponentially amplifies with the number of senders. We apply our results in a semi-device-independent protocol for robustly estimating the effective visibility of graph states and measurement bases. Overall, our approaches are robust to noise, can support the usage of uncharacterized state preparations or measurements, and can be applied to any graph state.
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BibTeX
@misc{doolittle2026robust,
title = {{Robust Entanglement Witnessing via Dense Network Coding with Graph States}},
author = {Brian Doolittle and Ian George},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.32024},
eprint = {2609.32024},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.32024},
}
RIS
TY - UNPB
TI - Robust Entanglement Witnessing via Dense Network Coding with Graph States
AU - Brian Doolittle
AU - Ian George
PY - 2026
DA - 2026/09/25
PB - arXiv
DO - 10.48550/arxiv.2609.32024
UR - https://arxiv.org/abs/2609.32024
AB - Practical tests for witnessing entanglement in the presence of noise are needed to verify and apply entanglement-based applications in real-world communication networks. Quantum dense network coding is a communication protocol that uses an entangled state preparation together with quantum communication to halve the amount of communication needed to evaluate certain bijective functions in networks having multiple senders and one receiver. In this work, we consider a dense network coding protocol that uses graph state entanglement to implement a family of affine transformations, we derive a bound on the success probability that can be achieved by classical networks, and we show that the noise robustness exponentially amplifies with the number of senders. We apply our results in a semi-device-independent protocol for robustly estimating the effective visibility of graph states and measurement bases. Overall, our approaches are robust to noise, can support the usage of uncharacterized state preparations or measurements, and can be applied to any graph state.
ER -