aiqbench analysis
This research addresses critical challenges in scaling quantum networks by solving the identifiability problem inherent in imperfect Bell-state measurements within star topologies. By deriving closed-form estimators and proving that specific probe designs maintain stable precision as network size grows, the study provides a theoretical foundation for reliable end-to-end error characterization. These findings are essential for advancing practical quantum communication infrastructure where measurement imperfections are unavoidable.
Identifiability and Estimation Precision in Quantum Network Tomography with Imperfect Bell-State Measurements
arXiv:2608.21692v1 Announce Type: new Abstract: We study Quantum Network Tomography (QNT) for end-to-end link-error characterization under imperfect Bell-state measurements (BSMs), where multiplicative coupling between link and measurement parameters makes identifiability non-trivial. For an n-node star network, we design probes that ensure unique identifiability and derive closed-form expressions for the Fisher Information Matrix (FIM) and Maximum Likelihood Estimators (MLEs), and characterize estimation precision through the Cramer-Rao Bound (CRB). The results show that BSM imperfections degrade estimation precision, while the proposed probes maintain nearly stable precision for individual link parameters as the network size increases. Monte Carlo simulations further confirm that the Mean Squared Error (MSE) approaches the CRB with increasing sample size.
Abstract:We study Quantum Network Tomography (QNT) for end-to-end link-error characterization under imperfect Bell-state measurements (BSMs), where multiplicative coupling between link and measurement parameters makes identifiability non-trivial. For an n-node star network, we design probes that ensure unique identifiability and derive closed-form expressions for the Fisher Information Matrix (FIM) and Maximum Likelihood Estimators (MLEs), and characterize estimation precision through the Cramer-Rao Bound (CRB). The results show that BSM imperfections degrade estimation precision, while the proposed probes maintain nearly stable precision for individual link parameters as the network size increases. Monte Carlo simulations further confirm that the Mean Squared Error (MSE) approaches the CRB with increasing sample size.
arXiv:2608.21692 [quant-ph]
(or arXiv:2608.21692v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2608.21692 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 197 words
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