دورية أكاديمية
Nearest centroid classification on a trapped ion quantum computer
| العنوان: | Nearest centroid classification on a trapped ion quantum computer |
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| المؤلفون: | Sonika Johri, Shantanu Debnath, Avinash Mocherla, Alexandros SINGK, Anupam Prakash, Jungsang Kim, Iordanis Kerenidis |
| المصدر: | npj Quantum Information, Vol 7, Iss 1, Pp 1-11 (2021) |
| بيانات النشر: | Nature Portfolio, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Physics LCC:Electronic computers. Computer science |
| مصطلحات موضوعية: | Physics, QC1-999, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: | Abstract 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2056-6387 |
| Relation: | https://doaj.org/toc/2056-6387 |
| DOI: | 10.1038/s41534-021-00456-5 |
| URL الوصول: | https://doaj.org/article/7ac446645ae74a218aaee8d6c4706aec |
| رقم الأكسشن: | edsdoj.7ac446645ae74a218aaee8d6c4706aec |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20566387 |
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| DOI: | 10.1038/s41534-021-00456-5 |