A digital twin of atomic ensemble quantum memories

TL;DR

This paper introduces a comprehensive digital twin framework for atomic ensemble quantum memories, enabling accurate performance estimation by modeling loss and noise, and demonstrating its application in quantum network protocols.

Contribution

The paper presents a novel quantum channel-based modeling framework for atomic quantum memories, including Kraus representations and performance metrics, compatible with existing quantum network simulation tools.

Findings

Kraus matrix representations for various quantum memories

Performance metrics for state-of-the-art memories

Successful simulation of a memory-assisted quantum token protocol

Abstract

Accurate performance estimation of experimentally demonstrated quantum memories is key to understand the nuances in their deployment in photonic quantum networks. While several software packages allow for accessible quantum simulation, they often do not account for the loss and noise in physical devices. We present a framework for modeling ensemble-based atomic quantum memories using the quantum channel formalism. We provide a Kraus matrix representation of several experimentally implemented state-of-the art quantum memories and give an overview of their most important performance metrics. To showcase the applicability of this approach, we implement a memory-assisted quantum token protocol within our simulation framework. Our digital twin model is readily extensible to other memory implementations and easily compatible with existing frameworks for performance simulation of experimental quantum networks.