标题： 中性原子和退火量子处理器上的聚类聚合算法 显示英文标题

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

摘要： 这项工作提出了一种混合量子-经典算法，用于执行聚类聚合，该算法专为中性原子量子计算机和量子退火器设计。 聚类聚合是一种减轻聚类算法弱点的技术，聚类算法是数据科学方法的重要类别，用于对数据集进行划分，并广泛应用于许多实际应用中。 通过将聚类聚合问题实例表示为最大独立集（MIS）问题和无约束二次二进制优化（QUBO）问题，可以利用Pasqal的Fresnel（中性原子处理器）和D-Wave的Advantage QPU（量子退火器）的潜力来解决这些问题。 此外，设计的聚类聚合算法首先在基于QuTiP的Fresnel模拟器上进行了验证，随后在Pasqal提供的基于张量网络的同一机器的模拟器上进行了验证。 结果揭示了技术限制，例如在使用的中性原子平台上添加额外约束的困难以及需要更好的度量标准来衡量生成的聚类质量。 然而，这项工作代表了朝着比较两种不同机器（量子退火器和中性原子量子计算机）的基准迈出的一步。 此外，研究结果表明混合量子-经典流水线在未来有令人期待的潜力，尽管量子和经典组件都需要进一步改进。 显示英文摘要

摘要： 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.