Identifiability and Estimation Precision in Quantum Network Tomography with Imperfect Bell-State Measurements

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.