Computable measure of the quantum correlation

TL;DR

This paper introduces a computable measure of quantum correlations based on the rank of the A-correlation matrix and Schatten p-norms, providing a practical way to quantify quantum discord and correlations.

Contribution

It develops a class of computable quantum correlation measures using Schatten p-norms, including a tight lower bound on geometric discord, improving quantification methods.

Findings

The measure captures quantum correlations effectively.

A vanishing lower bound indicates zero-discord states.

The measure is invariant under local reversible operations.

Abstract

A general state of an $m\otimes n$ system is a classical-quantum state if and only if its associated $A$-correlation matrix (a matrix constructed from the coherence vector of the party $A$, the correlation matrix of the state, and a function of the local coherence vector of the subsystem $B$), has rank no larger than $m-1$. Using the general Schatten $p$-norms, we quantify quantum correlation by measuring any violation of this condition. The required minimization can be carried out for the general $p$-norms and any function of the local coherence vector of the unmeasured subsystem, leading to a class of computable quantities which can be used to capture the quantumness of correlations due to the subsystem $A$. We introduce two special members of these quantifiers; The first one coincides with the tight lower bound on the geometric measure of discord, so that such lower bound fully captures the quantum correlation of a bipartite system. Accordingly, a vanishing tight lower bound on the geometric discord is a necessary and sufficient condition for a state to be zero-discord. The second quantifier has the property that it is invariant under a local and reversible operation performed on the unmeasured subsystem, so that it can be regarded as a computable well-defined measure of the quantum correlations. The approach presented in this paper provides a way to circumvent the problem with the geometric discord. We provide some examples to exemplify this measure.