Semi-device-independent channel identification with communication matrices

TL;DR

This paper introduces a semi-device-independent method for identifying and characterizing quantum channels using communication matrices, enabling channel differentiation and self-testing with limited setup information.

Contribution

It demonstrates how communication matrices can determine the informational completeness of a setup and facilitate quantum channel identification without full device characterization.

Findings

Communication matrix rank indicates setup's informational completeness.

Communication matrix 'information storability' enables self-testing of states and measurements.

Method allows semi-device-independent quantum channel identification.

Abstract

We look into the task of differentiating between any two quantum channels and reconstructing them from the obtained measurement statistics with possibly limited information about the experimental set-up. We employ the communication matrix formalism where the measurement statistics of a prepare-and-measure scenario is represented as a stochastic communication matrix. In order to differentiate between any two quantum channels, the informational completeness of the set-up is both necessary and sufficient. On the other hand, if we want to uniquely characterize any quantum channel, in addition we also need to have a complete description of the set-up. We show that in many important cases we can deduce this information directly from the communication matrix of the set-up before applying the channel. Given that we trust the dimension of the system, we show that we can deduce the information completeness of the set-up directly from the rank of the communication matrix. Furthermore, we show that another quantity of the communication matrix, called the information storability, can be used to self-test the set-up (up to unitary or antiunitary freedom) for an important class of states and measurements. This provides us a semi-device-independent way to identify quantum channels from the prepare-and-measure statistics. Lastly, we consider scenarios where we might have some additional information about the channels or additional resources at our disposal which could help us relax some of the assumptions of the proposed scenario.