output
20052026
most citedRemoving Leakage and Surface Recombination in Planar Perovskite Solar Cells

316 citations

40 papers

physics.optics2026

Comparison between methods to measureintensity modulator Vpi

Gilles Feugnet, Salma Essawab, Jimmy Pennanech +6

We describe and compare in this paper two common methods to measure the half-wave voltage (Vpi) of an electro-optical modulator versus RF frequency of the driving electronic signal…

physics.optics2025

Mid-infrared continua via spectral broadening and difference frequency generation in a nanophotonic lithium niobate waveguide

Markus Ludwig, Furkan Ayhan, Thibault Voumard +5

Periodically poled thin film lithium niobate waveguides provide simultaneous access to efficient second and third order nonlinear processes, enabling broadband generation of cohere…

cs.LG2025★ 1 cited

SolarCrossFormer: Improving day-ahead Solar Irradiance Forecasting by Integrating Satellite Imagery and Ground Sensors

Baptiste Schubnel, Jelena Simeunović, Corentin Tissier +2

Accurate day-ahead forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems into the power grid. However, current forecasting s…

physics.optics2024★ 15 cited

Ultrabroadband tunable difference frequency generation in standardized thin-film lithium niobate platform

Yesim Koyaz, Christian Lafforgue, Homa Zarebidaki +4

Thin-film lithium niobate (TFLN) on insulator is a promising platform for nonlinear photonic integrated circuits (PICs) due to its strong light confinement, high second-order nonli…

quant-ph2024★ 6 cited

Single-photon detectors on arbitrary photonic substrates

Max Tao, Hugo Larocque, Samuel Gyger +16

Detecting non-classical light is a central requirement for photonics-based quantum technologies. Unrivaled high efficiencies and low dark counts have positioned superconducting nan…

cs.CV2024★ 1 cited

PriPHiT: Privacy-Preserving Hierarchical Training of Deep Neural Networks

Yamin Sepehri, Pedram Pad, Pascal Frossard +1

The training phase of deep neural networks requires substantial resources and as such is often performed on cloud servers. However, this raises privacy concerns when the training d…