Entanglement buffering with multiple quantum memories

TL;DR

This paper analyzes the performance of entanglement buffers with multiple quantum memories, deriving analytical bounds and showing that frequent purification improves average fidelity, with simple protocols often outperforming complex ones.

Contribution

It provides analytical expressions and heuristics for optimizing entanglement buffering and purification policies in quantum networks.

Findings

Frequent purification maximizes average entanglement fidelity.

Simple protocols like DEJMPS often outperform complex fidelity-maximizing protocols.

Derived bounds serve as fundamental limits for entanglement buffer performance.

Abstract

Entanglement buffers are systems that maintain high-quality entanglement, ensuring it is readily available for consumption when needed. In this work, we study the performance of a two-node buffer, where each node has one long-lived quantum memory for storing entanglement and multiple short-lived memories for generating fresh entanglement. Newly generated entanglement may be used to purify the stored entanglement, which degrades over time. Stored entanglement may be removed due to failed purification or consumption. We derive analytical expressions for the system performance, which is measured using the entanglement availability and the average fidelity upon consumption. Our solutions are computationally efficient to evaluate, and they provide fundamental bounds to the performance of purification-based entanglement buffers. We show that purification must be performed as frequently as possible to maximise the average fidelity of entanglement upon consumption, even if this often leads to the loss of high-quality entanglement due to purification failures. Moreover, we obtain heuristics for the design of good purification policies in practical systems. A key finding is that simple purification protocols, such as DEJMPS, often provide superior buffering performance compared to protocols that maximize output fidelity.