Variational quantum cloning machine on an integrated photonic interferometer

TL;DR

This paper demonstrates an experimental implementation of a variational quantum cloning machine using integrated photonic interferometers, achieving near-optimal cloning performance through a programmable device and classical feedback.

Contribution

It introduces the first experimental realization of a variational quantum cloning machine on an integrated photonic platform, combining quantum machine learning with photonic quantum computing.

Findings

Achieved near-optimal cloning fidelities for phase-covariant and state-dependent cloning.

Utilized a fully programmable 6-mode integrated photonic device with classical feedback.

Showed potential of integrated photonics for variational quantum algorithms.

Abstract

A seminal task in quantum information theory is to realize a device able to produce copies of a generic input state with the highest possible output fidelity, thus realizing an \textit{optimal} quantum cloning machine. Recently, the concept of variational quantum cloning was introduced: a quantum machine learning algorithm through which, by exploiting a classical feedback loop informed by the output of a quantum processing unit, the system can self-learn the programming required for an optimal quantum cloning strategy. In this work, we experimentally implement a $1 \rightarrow 2$ variational cloning machine of dual-rail encoded photonic qubits, both for phase-covariant and state-dependent cloning. We exploit a fully programmable 6-mode universal integrated device and classical feedback to reach near-optimal cloning performances. Our results demonstrate the potential of programmable integrated photonic platforms for variational self-learning of quantum algorithms.