2022
Journal article  Open Access

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

Massoli F. V., Vadicamo L., Amato G., Falchi F.

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

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.

Source: ACM computing surveys (2022). doi:10.1145/3529756

Publisher: Association for Computing Machinery,, New York, N.Y. , Stati Uniti d'America


Metrics



Back to previous page
BibTeX entry
@article{oai:it.cnr:prodotti:472061,
	title = {A leap among quantum computing and quantum neural networks: a survey},
	author = {Massoli F. V. and Vadicamo L. and Amato G. and Falchi F.},
	publisher = {Association for Computing Machinery,, New York, N.Y. , Stati Uniti d'America},
	doi = {10.1145/3529756 and 10.48550/arxiv.2107.03313},
	journal = {ACM computing surveys},
	year = {2022}
}

AI4EU
A European AI On Demand Platform and Ecosystem

AI4Media
A European Excellence Centre for Media, Society and Democracy


OpenAIRE