Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction

Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reservoir, in which reservoir noise is used as a resource to generate expressive, nonlinear signals that are efficiently lear...

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Detalles Bibliográficos
Autores principales: Fry, Daniel, Deshmukh, Amol, Chen, Samuel Yen-Chi, Rastunkov, Vladimir, Markov, Vanio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630422/
https://www.ncbi.nlm.nih.gov/pubmed/37935730
http://dx.doi.org/10.1038/s41598-023-45015-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630422/
https://www.ncbi.nlm.nih.gov/pubmed/37935730
http://dx.doi.org/10.1038/s41598-023-45015-4

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