计算机科学中的量子机器学习教学

G. Luca, Yinong Chen
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引用次数: 2

摘要

量子计算领域正在迅速发展,短期内可以立即使用。量子计算在机器学习(即量子机器学习)中的应用也同样快速增长。噪声中尺度量子(NISQ)时代计算机的出现进一步推动了该领域的研究。从历史上看,对于计算机科学专业的学生或任何其他缺乏强大物理背景的学生来说,进入量子计算的障碍几乎是不可逾越的。然而,无论背景如何,量子计算和量子机器学习正变得越来越容易获得。本文的目标是展示和证明该领域对计算机科学专业的学生是可访问的,并提供一个示例课程。这个课程可以在一个独立的课程中使用,也可以作为另一个机器学习课程的一部分,正如作者所做的那样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Teaching Quantum Machine Learning in Computer Science
The field of quantum computing is rapidly growing, with near term applications immediately available for use. The application of quantum computing to machine learning (i.e., quantum machine learning) is similarly growing rapidly. The presence of noisy intermediate-scale quantum (NISQ) era computers is further enabling research in the area. Historically, the barrier to entry of quantum computing has been nearly insurmountable for computer science students, or any other students who lack a strong physics background. However, quantum computing and quantum machine learning are becoming increasingly accessible, regardless of background. The goal of this paper is to present and demonstrate that the field is accessible to computer science students and to provide a sample curriculum. This curriculum can be used in a standalone class or as part of another machine learning class, as the authors have done.
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