QUANTUM DEEP LEARNING OF CONVOLUTIONAL NEURAL NETWORK USING VARIATIONAL QUANTUM CIRCUIT
Abstract
Quantum computing in general and quantum deep learning represent a promising field re-lated to the research of modern methods and algorithms of quantum computing used for the pur-pose of teaching and developing new architectures of artificial neural networks. Recently, there has been a trend that research conducted in the field of quantum deep learning is becoming in-creasingly widespread among specialists. This can be explained by the fact that it has been estab-lished that quantum circuits are capable of functioning like artificial neural networks, while demonstrating the best results in solving several tasks, including, for example, the actual task of classifying objects in an image or in a video stream. Thanks to the rapid development of quantum computing in the field of deep learning, optimal solutions have been found for such urgent prob-lems as the vanishing gradient problem, finding a local minimum, improving the efficiency of large-scale parametric machine learning algorithms, eliminating decoherence and quantum er-rors, etc. Within the framework of this work, the process of functioning of a quantum variational scheme is described, its main characteristics are established, and disadvantages are identified. The key features of quantum computing, on which the process of implementing quantum deep learning with the reinforcement of a convolutional neural network is based, are also analyzed. In addition, quantum deep learning of a convolutional neural network has been carried out using a variational quantum scheme, which leads to an increase in the performance of a convolutional neural network in solving the problem of image processing, namely its classification, using a quantum computing environment. The relevance of this article consists in the implementation of a quantum deep learning algorithm with the reinforcement of a convolutional neural network for image processing, as well as the great importance of the subject of this study for the future devel-opment of quantum computing devices that can be used in artificial intelligence systems, etc., which corresponds to the priority direction of the development of domestic science
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