Berlin 2024 – scientific programme
Parts | Days | Selection | Search | Updates | Downloads | Help
DY: Fachverband Dynamik und Statistische Physik
DY 49: Focus Session: Computing with Dynamical Systems: New Perspectives on Reservoirs and Applications II – Applications and Quantum RC
DY 49.2: Talk
Thursday, March 21, 2024, 15:30–15:45, BH-N 243
Image classification using collective modes of a two-dimensional array of photonic-crystal nanolasers — •Giulio Tirabassi1, Kaiwen Ji2, Cristina Masoller1, and Alejandro Yacomotti2 — 1Departament de Fisica, Universitat Politecnica de Catalunya, Rambla Sant Nebridi 22, 08222 Terrassa, Barcelona, Spain — 2Centre de Nanosciences et de Nanotechnologies, CNRS, Universite Paris-Sud, Université Paris-Saclay, 10 Boulevard Thomas Gobert, 91120 Palaiseau, France
Optical computing is revolutionizing the fields of Artificial Intelligence (AI) and High-Performance Computing (HPC) systems. Due to their ultra-low power consumption, nanolasers are ideal light sources for AI and HPC systems. In particular, two-dimensional photonic-crystal nanolaser arrays can be designed and fabricated with evanescent coupling, whose strength can be precisely controlled by adjusting the radius of the holes that separate adjacent nanocavities. In this work, we exploit the collective modes of nanolaser arrays of different sizes for binary classification of images and data. Using a dataset of hand-written digits (a standard dataset for assessing the performance of image recognition systems), we show numerically that an overall success rate of 98% can be achieved in digit classification. Finally, going beyond simulations, we show with laboratory experiments that the performance of the nanolaser arrays can be comparable to that of common non-linear classification algorithms.
Keywords: Machine Learning; Nanolaser Arrays; Binary Classification