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A leap among quantum computing and quantum neural networks: a survey

Academic Article
Publication Date:
2022
abstract:
In recent years, Quantum Computing witnessed massive improvements in terms of available resources and algorithms development. The ability to harness quantum phenomena to solve computational problems is a long-standing dream that has drawn the scientific community's interest since the late 80s. In such a context, we propose our contribution. First, we introduce basic concepts related to quantum computations, and then we explain the core functionalities of technologies that implement the Gate Model and Adiabatic Quantum Computing paradigms. Finally, we gather, compare and analyze the current state-of-the-art concerning Quantum Perceptrons and Quantum Neural Networks implementations.
Iris type:
01.01 Articolo in rivista
Keywords:
Quantum Deep Learning; Quantum Machine Learning; Quantum Computing; Quantum Neural Network
List of contributors:
Massoli, FABIO VALERIO; Amato, Giuseppe; Falchi, Fabrizio; Vadicamo, Lucia
Authors of the University:
AMATO GIUSEPPE
FALCHI FABRIZIO
VADICAMO LUCIA
Handle:
https://iris.cnr.it/handle/20.500.14243/443600
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/443600/186541/prod_472061-doc_192023.pdf
Published in:
ACM COMPUTING SURVEYS
Journal
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URL

https://doi.org/10.1145/3529756
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