Measurement-based implementation makes entanglement purification based on hashing practical

TL;DR

This paper demonstrates that measurement-based implementations enable practical, high-yield entanglement purification protocols based on hashing, even with imperfect local operations and in noisy environments.

Contribution

It introduces a measurement-based approach to entanglement purification that remains effective under realistic noise conditions, extending to multiparty graph states.

Findings

Measurement-based schemes achieve nonzero yield with tolerable noise levels.

The approach is applicable to multiparty purification of arbitrary graph states.

Purification remains practical despite imperfections in local gates and measurements.

Abstract

We investigate entanglement purification protocols based on hashing, where a large number of noisy entangled pairs is jointly processed to obtain a reduced number of perfect, noiseless copies. While hashing and breeding protocols are the only purification protocols that asymptotically obtain a nonzero yield, they are not applicable in a realistic scenario if local gates and measurements are imperfect. We show that such problems can be overcome by a compact measurement-based implementation, yielding entanglement purification schemes with nonzero yield that are applicable also in noisy scenarios, with tolerable noise per particle of several percent. We also generalize these findings to multiparty purification protocols for arbitrary graph states.