计算机科学
量子机器学习
算法
量子计算机
人工智能
量子算法
机器学习
量子
量子信息
算法学习理论
作者
Glen S. Uehara,Andreas Spanias,William Clark
出处
期刊:International Conference on Information, Intelligence, Systems and Applications
日期:2021-07-12
卷期号:: 1-11
被引量:2
标识
DOI:10.1109/iisa52424.2021.9555570
摘要
Quantum Computing (QC) promises to elevate computing speed by an estimated 100 million times. Several applications, including signal processing, machine learning, big data, communication, and cryptography, will benefit from quantum computing. This paper provides a brief survey of quantum information processing algorithms with an emphasis on machine learning. We begin first, covering with an introduction to quantum systems. Then we describe briefly the fundamental blocks and principles of quantum mechanics, and we present several related QC concepts such as qubits, correlation, and entanglement. We also present simulations and tools for the quantum implementation of select algorithms. We cover specifically Quantum Machine Learning (QML) and demonstrate simple implementations. The paper also describes current research and provides an extensive bibliography for further reading.
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