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Springer eBooks

A Gentle Introduction to Quantum Machine Learning

Yuxuan Du, Xinbiao Wang, Naixu Guo, Zhan Yu, Qian Yang, Kaining Zhang, Min-Hsiu Hsieh, Patrick Rebentrost, Dacheng Tao

Published Jan 1, 2025• 6 citations
Publisher
DOI
10.1007/978-981-95-1284-3

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This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement). Building on that, foundational concepts of quantum machine learning (QML) are introduced (parametrized circuits, data encoding, and feature mapping). Then, QML models are discussed (quantum support vector machine, quantum feedforward neural network, and quantum convolutional neural network). All the aforementioned topics and concepts are examined using codes run on a quantum computer simulator. All the covered materials assume a novice audience interested in learning about QML. Further reading and software packages and frameworks are shared with the audience.
Quantum Machine Learning (QML) is popularly known to be an integrative approach to learning of the Quantum Physics (QP) and Machine Learning (ML). In this chapter, an outline of the fundamental ideas and features related to quantum machine learning is laid out. The different facets of quantum algorithms are discussed in this chapter. In addition to this, the basic features of quantum reinforcement learning and quantum annealing are also provided in this chapter. Finally, the chapter deliberates about the advancement of quantum neural networks to through light in the direction of QML.
The quantum race is on and the hype around quantum computing is only exceeded by artificial intelligence (AI). Tech giants, multinational corporations, and startups across a wide range of sectors, and even governments are betting on quantum technology, collaborating and competing to gain power that comes with having access to a quantum computer that can hopefully solve complex and relevant problems. But what is a quantum computer? How does it differ from a classical computer and why is it so difficult to build one? How could the realisation of such a mysterious machine represent power? Can quantum computing learn anything from the field of AI? This article answers these questions in a concise form without assuming any advanced knowledge in physics.