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pro vyhledávání: '"Riganti, Roberto"'
In this article, we employ multiscale physics-informed neural networks (MscalePINNs) for the inverse retrieval of the spatially inhomogeneous effective permittivity and for the homogenization of finite-size photonic media with stealthy hyperuniform (
Externí odkaz:
http://arxiv.org/abs/2405.07878
Autor:
Riganti, Roberto, Negro, Luca Dal
In this paper, we develop and employ auxiliary physics-informed neural networks (APINNs) to solve forward, inverse, and coupled integro-differential problems of radiative transfer theory (RTE). Specifically, by focusing on the relevant slab geometry
Externí odkaz:
http://arxiv.org/abs/2307.05602