Quantum Measurement Classification with Qudits

Autor:	Useche, Diego H., Giraldo-Carvajal, Andres, Zuluaga-Bucheli, Hernan M., Jaramillo-Villegas, Jose A., González, Fabio A.
Rok vydání:	2021
Předmět:	Quantum Physics Computer Science - Machine Learning
Zdroj:	Quantum Inf Process 21, 12 (2022)
Druh dokumentu:	Working Paper
DOI:	10.1007/s11128-021-03363-y
Popis:	This paper presents a hybrid classical-quantum program for density estimation and supervised classification. The program is implemented as a quantum circuit in a high-dimensional quantum computer simulator. We show that the proposed quantum protocols allow to estimate probability density functions and to make predictions in a supervised learning manner. This model can be generalized to find expected values of density matrices in high-dimensional quantum computers. Experiments on various data sets are presented. Results show that the proposed method is a viable strategy to implement supervised classification and density estimation in a high-dimensional quantum computer. Comment: 15 pages, 10 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2107.09781 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.