activity
20152025
most citedDeep learning in nano-photonics: inverse design and beyond

494 citations · 1.9k across the 37 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cond-mat.mes-hall2019★ 8 cited

Quantum Theory of Near-field Optical Imaging with Rare-earth Atomic Clusters

Clément Majorel, Christian Girard, Aurélien Cuche +2

Scanning near-field optical imaging (SNOM) using local active probes provides in general images of the electric part of the photonic local density of states. However, certain atomi…

cond-mat.mes-hall2019★ 16 cited

Polarizabilities of complex individual dielectric or plasmonic nanostructures

Adelin Patoux, Clément Majorel, Peter R. Wiecha +4

When the sizes of photonic nanoparticles are much smaller than the excitation wavelength, their optical response can be efficiently described with a series of polarizability tensor…

physics.comp-ph2019★ 271 cited

Deep learning meets nanophotonics: A generalized accurate predictor for near fields and far fields of arbitrary 3D nanostructures

Peter R. Wiecha, Otto L. Muskens

Deep artificial neural networks are powerful tools with many possible applications in nanophotonics. Here, we demonstrate how a deep neural network can be used as a fast, general p…

physics.app-ph2019★ 37 cited

Design of plasmonic directional antennas via evolutionary optimization

Peter R. Wiecha, Clément Majorel, Christian Girard +4

We demonstrate inverse design of plasmonic nanoantennas for directional light scattering. Our method is based on a combination of full-field electrodynamical simulations via the Gr…

eess.IV2019★ 59 cited

Deep Learning Enabled Real Time Speckle Recognition and Hyperspectral Imaging using a Multimode Fiber Array

Ulas Kürüm, P. R. Wiecha, Rebecca French +1

We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed…