Quantum Network Tomography

TL;DR

Quantum Network Tomography (QNT) is a crucial tool for characterizing errors in quantum networks, enabling improved system validation and error management through end-to-end error estimation.

Contribution

This paper provides an overview of QNT, applies a protocol for estimating quantum channel errors, and analyzes estimator performance, advancing quantum network error characterization methods.

Findings

QNT can estimate depolarizing channels in quantum star networks.

Performance analysis using QCRB and MSE shows estimator effectiveness.

Discussion highlights challenges and future directions in QNT research.

Abstract

Errors are the fundamental barrier to the development of quantum systems. Quantum networks are complex systems formed by the interconnection of multiple components and suffer from error accumulation. Characterizing errors introduced by quantum network components becomes a fundamental task to overcome their depleting effects in quantum communication. Quantum Network Tomography (QNT) addresses end-to-end characterization of link errors in quantum networks. It is a tool for building error-aware applications, network management, and system validation. We provide an overview of QNT and its initial results for characterizing quantum star networks. We apply a previously defined QNT protocol for estimating bit-flip channels to estimate depolarizing channels. We analyze the performance of our estimators numerically by assessing the Quantum Cram\`er-Rao Bound (QCRB) and the Mean Square Error (MSE) in the finite sample regime. Finally, we provide a discussion on current challenges in the field of QNT and elicit exciting research directions for future investigation.