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physics.optics2024
Multiscale Physics-Informed Neural Networks for the Inverse Design of Hyperuniform Optical Materials
Roberto Riganti, Yilin Zhu, Wei Cai +2
In this article, we employ multiscale physics-informed neural networks (MscalePINNs) for the inverse design of finite-size photonic materials with stealthy hyperuniform (SHU) disor…
physics.optics2023
Field theory description of the non-perturbative optical nonlinearity of epsilon-near-zero media
Yaraslau Tamashevich, Tornike Shubitidze, Luca Dal Negro +1
In this paper we introduce a fully non-perturbative approach for the description of the optical nonlinearity of epsilon-near-zero (ENZ) media. In particular, based on the rigorous…