On the correction of anomalous phase oscillation in entanglement witnesses using quantum neural networks

TL;DR

This paper introduces a quantum neural network approach to correct anomalous phase oscillations in entanglement witnesses, enabling more accurate detection of entanglement in two-qubit pure states.

Contribution

It presents a novel quantum neural network method to correct phase oscillations, improving entanglement detection beyond traditional witnesses.

Findings

Quantum neural networks can extract entanglement information.

The method corrects phase oscillations in entanglement indicators.

Enhanced accuracy in entanglement detection for two-qubit states.

Abstract

Entanglement of a quantum system depends upon relative phase in complicated ways, which no single measurement can reflect. Because of this, entanglement witnesses are necessarily limited in applicability and/or utility. We propose here a solution to the problem using quantum neural networks. A quantum system contains the information of its entanglement; thus, if we are clever, we can extract that information efficiently. As proof of concept, we show how this can be done for the case of pure states of a two-qubit system, using an entanglement indicator corrected for the anomalous phase oscillation. Both the entanglement indicator and the phase correction are calculated by the quantum system itself acting as a neural network.