Stochastic Multipath Routing for High-Throughput Entanglement Distribution in Quantum Repeater Networks

TL;DR

This paper introduces a stochastic multipath routing strategy for quantum repeater networks that improves entanglement distribution efficiency and scalability by probabilistically selecting paths, outperforming traditional single-path or globally optimized schemes.

Contribution

It proposes and analyzes a simple, scalable stochastic routing method that enhances entanglement rates and network utilization in quantum repeater networks.

Findings

Intermediate bias in path selection outperforms deterministic extremes.

The stochastic routing approach approaches capacity upper bounds.

Link usage becomes more balanced across the network.

Abstract

Quantum repeater networks distribute entanglement over lossy links while many users share a limited pool of entangled pairs. Most existing routing schemes either always use a single best path or rely on global optimizations that are hard to run in real time. Here we propose and analyze a simple alternative: a stochastic multipath rule in which each entanglement request is sent at random along one of several edge-disjoint repeater paths, with a single parameter that controls the bias between shorter and longer routes. Using a distance-dependent lossy network model with finite per-link capacities and probabilistic entanglement swapping, we develop an analytic description of the resulting end-to-end entanglement rate as a function of this bias and validate it with large-scale numerical simulations. We find that an intermediate bias consistently outperforms both deterministic extremes across distances, traffic patterns, attenuation, swapping noise, and congestion, bringing the rate close to simple capacity upper bounds and making link usage more even across networks. These results identify stochastic multipath routing as a lightweight classical control strategy for boosting performance and scalability in near-term quantum repeater networks.