Uncertainty decomposition of quantum networks in SLH framework

TL;DR

This paper introduces a systematic method to decompose uncertain quantum networks within the SLH framework into nominal and uncertain parts, facilitating robust stability analysis and bridging SLH modeling with state-space methods.

Contribution

It presents two decomposition theorems that enable the separation of uncertainties in SLH parameters into cascaded quantum network components, enhancing analysis capabilities.

Findings

Decomposition theorems for uncertain quantum networks.

Translation of uncertainties from SLH to state-space parameters.

Application to robust stability analysis.

Abstract

This paper presents a systematic method to decompose uncertain linear quantum input-output networks into uncertain and nominal subnetworks, when uncertainties are defined in SLH representation. To this aim, two decomposition theorems are stated, which show how an uncertain quantum network can be decomposed into nominal and uncertain subnetworks in cascaded connection and how uncertainties can be translated from SLH parameters into state-space parameters. As a potential application of the proposed decomposition scheme, robust stability analysis of uncertain quantum networks is briefly introduced. The proposed uncertainty decomposition theorems take account of uncertainties in all three parameters of a quantum network and bridge the gap between SLH modeling and state-space robust analysis theory for linear quantum networks.