Deep learning in nano-photonics: inverse design and beyond PR Wiecha, A Arbouet, C Girard, OL Muskens Photonics Research 9 (5), B182-B200, 2021 | 418 | 2021 |
Deep learning meets nanophotonics: a generalized accurate predictor for near fields and far fields of arbitrary 3D nanostructures PR Wiecha, OL Muskens Nano letters 20 (1), 329-338, 2019 | 249 | 2019 |
Evolutionary multi-objective optimization of colour pixels based on dielectric nanoantennas PR Wiecha, A Arbouet, C Girard, A Lecestre, G Larrieu, V Paillard Nature nanotechnology 12 (2), 163-169, 2017 | 145 | 2017 |
Pushing the limits of optical information storage using deep learning PR Wiecha, A Lecestre, N Mallet, G Larrieu Nature nanotechnology 14 (3), 237-244, 2019 | 125 | 2019 |
Enhanced luminescence properties of InAs–InAsP core–shell nanowires J Treu, M Bormann, H Schmeiduch, M Döblinger, S Morkötter, ... Nano letters 13 (12), 6070-6077, 2013 | 92 | 2013 |
Strongly directional scattering from dielectric nanowires PR Wiecha, A Cuche, A Arbouet, C Girard, G Colas des Francs, ... ACS photonics 4 (8), 2036-2046, 2017 | 84 | 2017 |
Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array U Kürüm, PR Wiecha, R French, OL Muskens Optics express 27 (15), 20965-20979, 2019 | 70 | 2019 |
pyGDM--A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures PR Wiecha Computer Physics Communications 233, 167-192, 2018 | 65 | 2018 |
Deep learning enabled design of complex transmission matrices for universal optical components NJ Dinsdale, PR Wiecha, M Delaney, J Reynolds, M Ebert, I Zeimpekis, ... ACS photonics 8 (1), 283-295, 2021 | 64 | 2021 |
Tailoring second-harmonic generation in single L-shaped plasmonic nanoantennas from the capacitive to conductive coupling regime LJ Black, PR Wiecha, Y Wang, CH De Groot, V Paillard, C Girard, ... ACS photonics 2 (11), 1592-1601, 2015 | 63 | 2015 |
InP-based type-II quantum-well lasers and LEDs S Sprengel, C Grasse, P Wiecha, A Andrejew, T Gruendl, G Boehm, ... IEEE Journal of Selected Topics in Quantum Electronics 19 (4), 1900909-1900909, 2013 | 51 | 2013 |
Chemical Vapor Deposition of High‐Optical‐Quality Large‐Area Monolayer Janus Transition Metal Dichalcogenides Z Gan, I Paradisanos, A Estrada‐Real, J Picker, E Najafidehaghani, ... Advanced Materials 34 (38), 2205226, 2022 | 42 | 2022 |
Origin of Second Harmonic Generation from individual Silicon Nanowires PR Wiecha, A Arbouet, C Girard, T Baron, V Paillard Physical Review B 93, 125421, 2016 | 39 | 2016 |
Design of plasmonic directional antennas via evolutionary optimization PR Wiecha, C Majorel, C Girard, A Cuche, V Paillard, OL Muskens, ... Optics express 27 (20), 29069-29081, 2019 | 38 | 2019 |
Enhanced nonlinear optical response from individual silicon nanowires PR Wiecha, A Arbouet, H Kallel, P Periwal, T Baron, V Paillard Physical Review B 91 (12), 121416, 2015 | 37 | 2015 |
Enhancement of electric and magnetic dipole transition of rare-earth-doped thin films tailored by high-index dielectric nanostructures PR Wiecha, C Majorel, C Girard, A Arbouet, B Masenelli, O Boisron, ... Applied optics 58 (7), 1682-1690, 2019 | 35 | 2019 |
Challenges in nanofabrication for efficient optical metasurfaces A Patoux, G Agez, C Girard, V Paillard, PR Wiecha, A Lecestre, ... Scientific reports 11 (1), 5620, 2021 | 28 | 2021 |
A newcomer’s guide to deep learning for inverse design in nano-photonics A Khaireh-Walieh, D Langevin, P Bennet, O Teytaud, A Moreau, ... Nanophotonics 12 (24), 4387-4414, 2023 | 27 | 2023 |
Decay rate of magnetic dipoles near nonmagnetic nanostructures PR Wiecha, A Arbouet, A Cuche, V Paillard, C Girard Physical Review B 97 (8), 085411, 2018 | 27 | 2018 |
Deep learning enabled strategies for modeling of complex aperiodic plasmonic metasurfaces of arbitrary size C Majorel, C Girard, A Arbouet, OL Muskens, PR Wiecha ACS photonics 9 (2), 575-585, 2022 | 26 | 2022 |