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A Leap among Quantum Computing and Quantum Neural Networks: A Survey

Authors: Massoli, Fabio Valerio; Vadicamo, Lucia; Amato, Giuseppe; Falchi, Fabrizio;

A Leap among Quantum Computing and Quantum Neural Networks: A Survey

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.

Country
Italy
Keywords

Quantum Neural Network, FOS: Computer and information sciences, Quantum Deep Learning, Quantum Physics, Computer Science - Emerging Technologies, FOS: Physical sciences, Machine Learning (stat.ML), I.2.0, Emerging Technologies (cs.ET), Statistics - Machine Learning, Quantum Computing, Quantum Physics (quant-ph), Quantum Deep Learning, Quantum Machine Learning, Quantum Computing, Quantum Neural Network, Quantum Machine Learning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
43
Top 10%
Top 10%
Top 1%
11
13
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