Diagrammatic technique for simulation of large-scale quantum repeater networks with dissipating quantum memories

TL;DR

This paper introduces a diagrammatic semi-analytical technique for simulating large-scale quantum repeater networks, accounting for imperfections and dissipative dynamics, enabling efficient network optimization.

Contribution

It presents a novel diagrammatic method that accurately models quantum networks with reduced computational complexity compared to traditional simulations.

Findings

Method matches Monte Carlo simulations in accuracy.

Computational resources scale linearly with network size.

Enables efficient optimization of quantum networks.

Abstract

We present a detailed description of the diagrammatic technique, recently devised in [V. V. Kuzmin et.al., npj Quantum Information 5, 115 (2019)], for semi-analytical description of large-scale quantum-repeater networks. The technique takes into account all essential experimental imperfections, including dissipative Liouville dynamics of the network quantum memories and the classical communication delays. The results obtained with the semi-analytic method match the exact Monte Carlo simulations while the required computational resources scale only linearly with the network size. The presented approach opens new possibilities for the development and efficient optimization of future quantum networks.