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Deep learning in nano-photonics: inverse design and beyond
Deep learning in the context of nano-photonics is mostly discussed in terms of its potential
for inverse design of photonic devices or nano-structures. Many of the recent works on …
for inverse design of photonic devices or nano-structures. Many of the recent works on …
Deep learning the electromagnetic properties of metamaterials—a comprehensive review
Deep neural networks (DNNs) are empirically derived systems that have transformed
traditional research methods, and are driving scientific discovery. Artificial electromagnetic …
traditional research methods, and are driving scientific discovery. Artificial electromagnetic …
Physics-informed machine learning: A survey on problems, methods and applications
[HTML][HTML] Roadmap on photonic metasurfaces
Here we present a roadmap on Photonic metasurfaces. This document consists of a number
of perspective articles on different applications, challenge areas or technologies underlying …
of perspective articles on different applications, challenge areas or technologies underlying …
Intelligent designs in nanophotonics: from optimization towards inverse creation
Applying intelligence algorithms to conceive nanoscale meta-devices becomes a flourishing
and extremely active scientific topic over the past few years. Inverse design of functional …
and extremely active scientific topic over the past few years. Inverse design of functional …
A newcomer's guide to deep learning for inverse design in nano-photonics
Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as
light concentration, routing, and filtering. Designing these devices to achieve precise light …
light concentration, routing, and filtering. Designing these devices to achieve precise light …
Neural operator-based surrogate solver for free-form electromagnetic inverse design
Neural operators have emerged as a powerful tool for solving partial differential equations in
the context of scientific machine learning. Here, we implement and train a modified Fourier …
the context of scientific machine learning. Here, we implement and train a modified Fourier …