Estimating the degree of non-Markovianity using variational quantum circuits

TL;DR

This paper presents a method using variational quantum circuits to estimate the non-Markovianity of quantum environments by optimizing qubit-environment interactions, enabling practical quantum diagnostics.

Contribution

It introduces a novel variational quantum circuit approach with a problem-based ansatz for accurately estimating non-Markovianity in quantum systems.

Findings

Accurate estimation of non-Markovianity for amplitude and phase damping models.

Optimal qubit-environment interaction sequences identified.

Feasible experimental procedure proposed for non-Markovianity measurement.

Abstract

Several applications of quantum machine learning (QML) rely on a quantum measurement followed by training algorithms using the measurement outcomes. However, recently developed QML models, such as variational quantum circuits (VQCs), can be implemented directly on the state of the quantum system (quantum data). Here, we propose to use a qubit as a probe to estimate the degree of non-Markovianity of the environment. Using VQCs, we find an optimal sequence of qubit-environment interactions that yield accurate estimations of the degree of non-Markovianity for the amplitude damping, phase damping, and the combination of both models. We introduce a problem-based ansatz that optimizes upon the probe qubit and the interaction time with the environment. This work contributes to practical quantum applications of VQCs and delivers a feasible experimental procedure to estimate the degree of non-Markovianity.