How confused can an entanglement witness be to be still persuasive

TL;DR

This paper explores how artificial neural networks can effectively detect entanglement in quantum states, offering a practical balance between accuracy and efficiency compared to traditional witness-based methods, demonstrated on both simulated and real data.

Contribution

It introduces ANN as a reliable alternative to entanglement witnesses for general quantum states without prior information, validated through comparative analysis and experimental data.

Findings

ANN outperforms traditional witnesses in accuracy

ANN requires less computational effort than full tomography

Effective on both simulated and real quantum data

Abstract

Detection of entangled states is essential in both fundamental and applied quantum physics. However, this task proves to be challenging especially for general quantum states. One can execute full state tomography but this method is time demanding especially in complex systems. Other approaches use entanglement witnesses, these methods tend to be less demanding but lack reliability. Here, we demonstrate that ANN -- artificial neural networks provide a balance between both approaches. In this paper, we make a comparison of ANN performance against witness-based methods for random general 2-qubit quantum states without any prior information on the states. Furthermore, we apply our approach to real experimental data set.