自适应量子核主成分分析在化学电阻传感器阵列中的应用（ei）

IF 14.3 1区材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Advanced Science Pub Date : 2025-04-17 DOI:10.1002/advs.202570102

Zeheng Wang, Timothy van der Laan, Muhammad Usman

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引用次数: 0

摘要

量子机器学习在2411573号文章中，王泽恒、Timothy van der Laan和Muhammad Usman介绍了一个量子算法驱动的框架来压缩化学电阻传感器数据。通过采用自适应量子核（SAQK），将经典数据映射到量子态空间，在量子态空间中使用量子主成分分析（qPCA）实现显著的降维。这种创新的方法不仅最大限度地减少了信息丢失，而且提高了随后人工智能驱动的读出精度。这项工作强调了量子算法和人工智能的协同作用，为在嘈杂的中等规模量子（NISQ）设备上高效处理物联网数据铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Self-Adaptive Quantum Kernel Principal Component Analysis for Compact Readout of Chemiresistive Sensor Arrays (Adv. Sci. 15/2025)

查看原文本刊更多论文

Self-Adaptive Quantum Kernel Principal Component Analysis for Compact Readout of Chemiresistive Sensor Arrays (Adv. Sci. 15/2025)

Quantum Machine Learning

In article number 2411573, Zeheng Wang, Timothy van der Laan, and Muhammad Usman introduce a quantum algorithm-driven framework to compress chemiresistive sensor data. By employing a self-adaptive quantum kernel (SAQK), classical data are mapped into a quantum state space, where quantum principal component analysis (qPCA) is used to achieve significant dimensionality reduction. This innovative method not only minimizes information loss but also improves the subsequent AI-driven readout accuracy. The work highlights the synergy of quantum algorithms and AI, paving the way for efficient IoT data handling on noisy intermediate-scale quantum (NISQ) devices.

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来源期刊

Advanced Science CHEMISTRY, MULTIDISCIPLINARYNANOSCIENCE &-NANOSCIENCE & NANOTECHNOLOGY

CiteScore

18.90

自引率

2.60%

发文量

1602

审稿时长

1.9 months

期刊介绍： Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.