On the Characterization of Quantum Flip Stars with Quantum Network Tomography

TL;DR

This paper develops and analyzes quantum network tomography protocols for star-shaped quantum networks affected by bit-flip noise, introducing methods to characterize noise and assess protocol efficiency, including the role of entanglement.

Contribution

It proposes novel tomography protocols for quantum star networks with bit-flip noise, including separate design of state distribution and measurements, and introduces a theoretical benchmark for protocol efficiency.

Findings

Protocols' efficiency depends on parameter regimes.

Entanglement may offer benefits in quantum network tomography.

Simulations show convergence properties of estimators.

Abstract

The experimental realization of quantum information systems will be difficult due to how sensitive quantum information is to noise. Overcoming this sensitivity is central to designing quantum networks capable of transmitting quantum information reliably over large distances. Moreover, the ability to characterize communication noise in quantum networks is crucial in developing network protocols capable of overcoming the effects of noise in quantum networks. In this context, quantum network tomography refers to the characterization of channel noise in a quantum network through end-to-end measurements. In this work, we propose network tomography protocols for quantum star networks formed by quantum channels characterized by a single, non-trivial Pauli operator. Our results further the end-to-end characterization of quantum bit-flip star networks by introducing tomography protocols where state distribution and measurements are designed separately. We build upon previously proposed quantum network tomography protocols, as well as provide novel methods for the unique characterization of bit-flip probabilities in stars. We introduce a theoretical benchmark based on the Quantum Fisher Information matrix to compare the efficiency of quantum network protocols. We apply our techniques to the protocols proposed, and provide an initial analysis on the potential benefits of entanglement for Quantum Network Tomography. Furthermore, we simulate the proposed protocols using NetSquid to assess the convergence properties of the estimators obtained for particular parameter regimes. Our findings show that the efficiency of protocols depend on parameter values and motivate the search for adaptive quantum network tomography protocols.