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What is Quantum Neural Network

Chapter 4
Technology Road Mapping for Quantum Computing and Engineering
The quantum neural network is a computational neural network that is based on quantum mechanics. Machine learning algorithms and quantum neural networks (QNN) combine concepts from quantum computing and artificial neural networks. In the past decade, the term has been applied to describe a variety of ideas, ranging from quantum computers that emulate the exact functions of neural nets to general trainable quantum circuits that bear little resemblance to the multilayer structure of perceptron.
Published in Chapter:
A Taxonomy of Quantum Computing Algorithms: Advancements and Anticipations
Lopamudra Hota (National Institute of Technology, Rourkela, India) and Prasant Kumar Dash (C. V. Raman Global University, India)
Copyright: © 2022 |Pages: 21
DOI: 10.4018/978-1-7998-9183-3.ch004
Abstract
Quantum computing exploits quantum-mechanical principles such as entanglement and superposition to offer significant computational advantages over conventional classical computing. Many complex and computationally challenging problems are expected to be solved by quantum computing in a number of fields, such as data science, industrial chemistry, smart energy, finance, secure communications, and many others. In order to understand the current status of quantum computing and identify its challenges, a systematic review of the existing literature will be valuable. An overview of quantum computing literature and its taxonomy is presented in this chapter. Further, the proposed taxonomy aims to identify research gaps by mapping various related studies. There is a detailed analysis of quantum technologies with the most current state of the art. Finally, the chapter presents a highlight of open challenges and future research directions.
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