.png){kind=icon}
返回
Nearest centroid classification on a trapped ion quantum computer
.png){kind=icon}
OA
AI
DOI：10.1038/s41534-021-00456-5.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Quantum machine learning has seen considerable theoretical and practical developments in recent years and has become a promising area for finding real world applications of quantum computers. In pursuit of this goal, here we combine state-of-the-art algorithms and quantum hardware to provide an experimental demonstration of a quantum machine learning application with provable guarantees for its performance and efficiency. In particular, we design a quantum Nearest Centroid classifier, using techniques for efficiently loading classical data into quantum states and performing distance estimations, and experimentally demonstrate it on a 11-qubit trapped-ion quantum machine, matching the accuracy of classical nearest centroid classifiers for the MNIST handwritten digits dataset and achieving up to 100% accuracy for 8-dimensional synthetic data.
Keyword:
2-QUBIT GATES
CIRCUITS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.3
论文数:
1.4K
被引数:
8.1K
机构
引用论文
Teladorsagiosis in young lambs and extended postparturient susceptibility in moxidectin‐treated ewes grazing heavily contaminated pastures泰拉尔萨吉亚病在幼龄羊中，以及在高污染牧场放牧的莫西多克丁治疗过的母羊中出现的产后易感期延长现象。
PREAI
分享收藏Quantum semi-supervised generative adversarial network for enhanced data classification.png)
SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏分享收藏
查看更多内容