Efficient Routing on Quantum Networks Using Adaptive Clustering

We introduce QuARC, Quantum Adaptive Routing using Clusters, a novel clustering-based entanglement routing protocol that leverages redundant, multi-path routing through multi-particle projective quantum measurements to enable high-throughput, low-overhead, starvation-free entanglement distribution. At its core, QuARC periodically reconfigures the underlying quantum network into clusters of different sizes, where each cluster acts as a small network that distributes entanglement across itself, and the end-to-end entanglement is established by further distributing between clusters. QuARC does not require a-priori knowledge of any physical parameters, and is able to adapt the network configuration using static topology information, and using local (within-cluster) measurements only. We present a comprehensive simulation-based evaluation that shows QuARC is robust against changes to physical network parameters, and maintains high throughput without starvation even as network sizes scale and physical parameters degrade.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/icnp61940.2024.10858533
Citations
4
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
1.39
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article

Efficient Routing on Quantum Networks Using Adaptive Clustering

Connor Clayton, Bobby Bhattacharjee, Xiaodi Wu
4 citations
Quantum Computing Algorithms and Architecture
1.39
article

Efficient Routing on Quantum Networks Using Adaptive Clustering

Connor Clayton, Bobby Bhattacharjee, Xiaodi Wu
article en
4 citations

Abstract

We introduce QuARC, Quantum Adaptive Routing using Clusters, a novel clustering-based entanglement routing protocol that leverages redundant, multi-path routing through multi-particle projective quantum measurements to enable high-throughput, low-overhead, starvation-free entanglement distribution. At its core, QuARC periodically reconfigures the underlying quantum network into clusters of different sizes, where each cluster acts as a small network that distributes entanglement across itself, and the end-to-end entanglement is established by further distributing between clusters. QuARC does not require a-priori knowledge of any physical parameters, and is able to adapt the network configuration using static topology information, and using local (within-cluster) measurements only. We present a comprehensive simulation-based evaluation that shows QuARC is robust against changes to physical network parameters, and maintains high throughput without starvation even as network sizes scale and physical parameters degrade.

University of Maryland, College Park (US)
Affordable and clean energy
Openalex Percentile: Top 15%
Quantum Computing Algorithms and Architecture
1.39
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Efficient Routing on Quantum Networks Using Adaptive Clustering — Connor Clayton, Bobby Bhattacharjee, et al. · (2024) | TGRS Research Map | TGRS