Discrimination strategies for inequivalent classes of multipartite entangled states

TL;DR

This paper introduces methods to experimentally distinguish inequivalent classes of multipartite entangled states using expectation value differences and relative entropy measures, with a focus on graph states.

Contribution

It proposes a framework for discriminating entanglement classes experimentally, utilizing stabilizer formalism to optimize measurement strategies.

Findings

Two measures for discrimination strength are introduced: expectation value difference and relative entropy.

The approach is applied to graph states using stabilizer formalism to identify optimal observables.

The methods are suitable for experiments with limited resources.

Abstract

How can one discriminate different inequivalent classes of multiparticle entanglement experimentally? We present an approach for the discrimination of an experimentally prepared state from the equivalence class of another state. We consider two possible measures for the discrimination strength of an observable. The first measure is based on the difference of expectation values, the second on the relative entropy of the probability distributions of the measurement outcomes. The interpretation of these measures and their usefulness for experiments with limited resources are discussed. In the case of graph states, the stabilizer formalism is employed to compute these quantities and to find sets of observables that result in the most decisive discrimination.