Presentation
20 June 2024 Exciton–polariton condensates for photonic spiking neurons
Author Affiliations +
Abstract
Spiking neural networks are a class of artificial neural networks maintaining a strict analogy to brain-like processing. I’ll show a new hardware approach in which semiconductor microcavities in strong light-matter coupling regime can operate as optical spiking neurons. We demonstrated the intrinsic property of exciton-polaritons to resemble the Leaky Integrate-and-Fire spiking mechanism. Polaritons when pumped with a pulsed laser exhibit leaky-integration due to relaxation of the excitonic reservoir, threshold-and-fire mechanism due to transition to polariton condensate, and resetting due to stimulated emission of photons. Our approach provides means for energy-efficient ultrafast processing of spike-like laser pulses at the level below 1 pJ/spike.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Barbara Pietka, Krzysztof Tyszka, Magdalena Furman, Andrzej Opala, Rafal Mirek, Mateusz Król, Jan Suffczynski, Wojciech Pacuski, Jacek Szczytko, and Michal Matuszewski "Exciton–polariton condensates for photonic spiking neurons", Proc. SPIE PC13004, Nonlinear Optics and its Applications 2024, PC130040B (20 June 2024); https://doi.org/10.1117/12.3023211
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KEYWORDS
Neurons

Artificial neural networks

Laser processing

Polaritons

Ultrafast phenomena

Optical microcavities

Photons

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