Cargando…
Flexible learning of quantum states with generative query neural networks
Deep neural networks are a powerful tool for characterizing quantum states. Existing networks are typically trained with experimental data gathered from the quantum state that needs to be characterized. But is it possible to train a neural network offline, on a different set of states? Here we intro...
Autores principales: | Zhu, Yan, Wu, Ya-Dong, Bai, Ge, Wang, Dong-Sheng, Wang, Yuexuan, Chiribella, Giulio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584912/ https://www.ncbi.nlm.nih.gov/pubmed/36266334 http://dx.doi.org/10.1038/s41467-022-33928-z |
Ejemplares similares
-
Quantum theory informational foundations and foils
por: Chiribella, Giulio, et al.
Publicado: (2016) -
Quantum speedup in the identification of cause–effect relations
por: Chiribella, Giulio, et al.
Publicado: (2019) -
Quantum theory from first principles: an informational approach
por: D'Ariano, Giacomo Mauro, et al.
Publicado: (2017) -
Device-independent certification of indefinite causal order in the quantum switch
por: van der Lugt, Tein, et al.
Publicado: (2023) -
Agents, Subsystems, and the Conservation of Information
por: Chiribella, Giulio
Publicado: (2018)