随着计算机能力的提高和算法的进步，机器学习技术已经成为寻找数据模式的有力工具。量子系统可以在数据中产生被认为经典系统不能有效地产生的非典型模式，所以有理由认为量子计算机在机器学习任务上可能胜过经典计算机。量子机器学习领域探索如何设计和实现能够使机器学习比经典计算机更快的量子软件。最近的工作已经产生了可以作为机器学习程序的基石的量子算法，但是硬件和软件的挑战仍然相当大。

（2017年9月23日）

量子机器学习入门：

http://blog.sciencenet.cn/blog-3364677-1096172.html

量子最快入门教程：

http://blog.sciencenet.cn/home.php?mod=space&uid=3364677&do=blog&id=1084559&from=space

Quantum machine learning

原文来源：http://www.nature.com/nature/journal/v549/n7671/full/nature23474.html

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.