Optimization of QKD Networks with Classical and Quantum Annealing

TL;DR

This paper compares classical and quantum annealing methods to optimize the deployment of QKD hardware in networks, aiming to meet security, redundancy, and latency requirements efficiently.

Contribution

It introduces a novel optimization approach using classical and quantum annealing for planning QKD network deployment considering multiple constraints.

Findings

Quantum annealing offers a promising approach for QKD network optimization.

The heuristic can effectively balance security, redundancy, and latency.

Classical methods provide a baseline for comparison.

Abstract

This paper analyses a classical and a quantum annealing approach to compute the minimum deployment of Quantum Key Distribution (QKD) hardware in a tier 1 provider network. The ensemble of QKD systems needs to be able to exchange as many encryption keys between all network nodes in order to encrypt the data payload, which is defined by traffic demand matrices. Redundancy and latency requirements add additional boundary conditions. The result of the optimization problem yields a classical heuristic network planners may utilize for planning future QKD quantum networks.