A clustering aggregation algorithm on neutral-atoms and annealing quantum processors

TL;DR

This paper introduces a hybrid quantum-classical clustering aggregation algorithm tailored for neutral-atoms and annealing quantum processors, demonstrating initial validation and highlighting technical challenges and future potential.

Contribution

It presents a novel approach to solve clustering aggregation problems using neutral-atom and annealing quantum processors, bridging different quantum hardware types.

Findings

Validated on Pasqal's Fresnel emulator and tensor network emulator

Identified technical limitations in adding constraints on neutral-atom platforms

Highlighted the need for better metrics to evaluate clustering quality

Abstract

This work presents a hybrid quantum-classical algorithm to perform clustering aggregation, designed for neutral-atoms quantum computers and quantum annealers. Clustering aggregation is a technique that mitigates the weaknesses of clustering algorithms, an important class of data science methods for partitioning datasets, and is widely employed in many real-world applications. By expressing the clustering aggregation problem instances as a Maximum Independent Set (MIS) problem and as a Quadratic Unconstrained Binary Optimization (QUBO) problem, it was possible to solve them by leveraging the potential of Pasqal's Fresnel (neutral-atoms processor) and D-Wave's Advantage QPU (quantum annealer). Additionally, the designed clustering aggregation algorithm was first validated on a Fresnel emulator based on QuTiP and later on an emulator of the same machine based on tensor networks, provided by Pasqal. The results revealed technical limitations, such as the difficulty of adding additional constraints on the employed neutral-atoms platform and the need for better metrics to measure the quality of the produced clusterings. However, this work represents a step towards a benchmark to compare two different machines: a quantum annealer and a neutral-atom quantum computer. Moreover, findings suggest promising potential for future advancements in hybrid quantum-classical pipelines, although further improvements are needed in both quantum and classical components.