Entanglement characterization by single-photon counting with random noise

TL;DR

This paper explores entanglement characterization using polarization measurements and maximum likelihood estimation, analyzing the robustness of the technique under various noise conditions including random errors and dark counts.

Contribution

It introduces a comprehensive framework for entanglement characterization that accounts for realistic measurement noise and evaluates its performance with numerical simulations.

Findings

The method effectively estimates entanglement even with significant noise.

Quantum fidelity remains high under moderate noise levels.

Concurrence accurately reflects entanglement preservation in noisy scenarios.

Abstract

In this article, we investigate the problem of entanglement characterization with polarization measurements combined with maximum likelihood estimation (MLE). A realistic scenario is considered with measurement results distorted by random experimental errors. In particular, by imposing unitary rotations acting on the measurement operators, we can test the performance of the tomographic technique versus the amount of noise. Then, dark counts are introduced to explore the efficiency of the framework in a multi-dimensional noise scenario. The concurrence is used as a figure of merit to quantify how well entanglement is preserved through noisy measurements. Quantum fidelity is computed to quantify the accuracy of state reconstruction. The results of numerical simulations are depicted on graphs and discussed.