Introducción a Machine Learning Cuántico

Abstract

In this paper we will explore how some machine learning algorithms can be improved, quadratically and exponentially, thanks to quantum computing. There is a brief introduction to the world of data and why it is important to perform an adequate processing of them, and laying the foundations for both machine learning and quantum computing, the implementation of a support vector machine algorithm (SVM) in a quantum simulator will be described and shown, capable of recognizing and classifying images of digits 6 and 9, developed and implemented physically by Zhaokai Li, Xiaomei Liu, Nanyang Xu, Jiangfeng Du, at the University of Science and Technology from China, Hefei, demonstrating how one can have an exponential improvement in temporal complexity with respect to its classical counterpart.