Characterizing arbitrary quantum networks in the noisy intermediate-scale quantum era

TL;DR

This paper introduces a systematic approach to characterize arbitrary quantum networks in the noisy intermediate-scale quantum (NISQ) era, addressing noise and scalability issues with new tools based on purity, covariance, and topology.

Contribution

It develops a feasible method for analyzing noisy, intermediate-scale, and sparse quantum networks, extending beyond idealized models.

Findings

Can witness the quality of multipartite entangled sources

Effective in noisy and sparse quantum network scenarios

Provides insights into quantum memory performance

Abstract

Quantum networks are of high interest nowadays. In short, they describe the distribution of quantum sources represented by edges to different parties represented by nodes in the networks. Bundles of tools have been developed recently to characterize quantum states from the network in the ideal case. However, features of quantum networks in the noisy intermediate-scale quantum (NISQ) era invalidate most of them and call for feasible tools. By utilizing purity, covariance, and topology of quantum networks, we provide a systematic approach to tackle with arbitrary quantum networks in the NISQ era, which can be noisy, intermediate-scale, random, and sparse. One application of our method is to witness the progress of essential elements in quantum networks, like the quality of multipartite entangled sources and quantum memory.