利用轮廓核心集和变分量子求解器进行聚类

IF 4.4 Q1 OPTICS Advanced quantum technologies Pub Date : 2024-06-16 DOI:10.1002/qute.202300450
Canaan Yung, Muhammad Usman
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引用次数: 0

摘要

最近的研究提出通过量子近似优化算法(QAOA)和核心集技术在量子计算机上解决 k-means 聚类问题。虽然目前的方法证明了量子 k-means 聚类的可能性,但它不能确保在各种数据集上的高准确性和一致性。现有的核心集技术是为经典算法设计的,还没有量子定制核心集技术来提高量子算法的准确性。本研究提出用变分量子求解器(VQE)和一种定制的核心集方法(Contour 核心集)来解决 k-means 聚类问题。利用合成数据和真实数据进行的大量仿真表明,VQE+Contour 核心集方法优于现有的 QAOA+Coreset k-means 聚类方法,具有更高的准确度和更低的标准偏差。这项研究表明,与通用的现成核心集技术相比,量子定制核心集技术能显著提高量子算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Clustering by Contour Coreset and Variational Quantum Eigensolver

Recent work has proposed solving the k-means clustering problem on quantum computers via the Quantum Approximate Optimization Algorithm (QAOA) and coreset techniques. Although the current method demonstrates the possibility of quantum k-means clustering, it does not ensure high accuracy and consistency across a wide range of datasets. The existing coreset techniques are designed for classical algorithms, and there is no quantum-tailored coreset technique designed to boost the accuracy of quantum algorithms. This study proposes solving the k-means clustering problem with the variational quantum eigensolver (VQE) and a customized coreset method, the Contour coreset, which is formulated with a specific focus on quantum algorithms. Extensive simulations with synthetic and real-life data demonstrated that the VQE+Contour Coreset approach outperforms existing QAOA+Coreset k-means clustering approaches with higher accuracy and lower standard deviation. This research demonstrates that quantum-tailored coreset techniques can remarkably boost the performance of quantum algorithms compared to generic off-the-shelf coreset techniques.

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CiteScore
7.90
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期刊最新文献
Front Cover: Laser Beam Induced Charge Collection for Defect Mapping and Spin State Readout in Diamond (Adv. Quantum Technol. 12/2024) Inside Front Cover: Numerical Investigation of a Coupled Micropillar - Waveguide System for Integrated Quantum Photonic Circuits (Adv. Quantum Technol. 12/2024) Back Cover: Purity-Assisted Zero-Noise Extrapolation for Quantum Error Mitigation (Adv. Quantum Technol. 12/2024) Issue Information (Adv. Quantum Technol. 12/2024) Issue Information (Adv. Quantum Technol. 11/2024)
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