Toward a quantum computing algorithm to quantify classical and quantum correlation of system states

Abstract

Optimal measurement is required to obtain the quantum and classical correlations of a quantum state, and the crucial difficulty is how to acquire the maximal information about one system by measuring the other part; in other words, getting the maximum information corresponds to preparing the best measurement operators. Within a general setup, we designed a variational hybrid quantum–classical algorithm to achieve classical and quantum correlations for system states under the Noisy-Intermediate Scale Quantum technology. To employ, first, we map the density matrix to the vector representation, which displays it in a doubled Hilbert space, and it is converted to a pure state. Then, we apply the measurement operators to a part of the subsystem and use variational principle and a classical optimization for the determination of the amount of correlation. We numerically test the performance of our algorithm at finding a correlation of some density matrices, and the output of our algorithm is compatible with the exact calculation.