Optimal resource allocation for flexible-grid entanglement distribution networks

TL;DR

This paper presents a genetic algorithm-based method for optimizing resource allocation in flexible-grid quantum networks to enhance entanglement distribution, validated through experiments and theoretical bounds.

Contribution

Introduces a general model for entanglement distribution in flex-grid quantum networks and applies a genetic algorithm for optimal resource provisioning.

Findings

Derived upper bounds on fidelity and entangled bit rate.

Validated model features experimentally in a deployed fiber network.

Demonstrated rapid design potential for large-scale networks.

Abstract

We use a genetic algorithm (GA) as a design aid for determining the optimal provisioning of entangled photon spectrum in flex-grid quantum networks with arbitrary numbers of channels and users. After introducing a general model for entanglement distribution based on frequency-polarization hyperentangled biphotons, we derive upper bounds on fidelity and entangled bit rate for networks comprising one-to-one user connections. Simple conditions based on user detector quality and link efficiencies are found that determine whether entanglement is possible. We successfully apply a GA to find optimal resource allocations in four different representative network scenarios and validate features of our model experimentally in a quantum local area network in deployed fiber. Our results show promise for the rapid design of large-scale entanglement distribution networks.