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Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Sedykh, Alexandr, Podapaka, Maninadh, Sagingalieva, Asel, Pinto, Karan, Pflitsch, Markus, Melnikov, Alexey
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Fluid Dynamics Quantum Physics
Accès en ligne:	Acceder al recurso
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