光子学
纳米晶材料
光子
材料科学
光电子学
纳米技术
光学
物理
作者
Artur Bednarkiewicz,Marcin Szalkowski,Martyna Majak,Zuzanna Korczak,Małgorzata Misiak,Sebastian Maćkowski
出处
期刊:CERN European Organization for Nuclear Research - Zenodo
日期:2023-10-31
标识
DOI:10.5281/zenodo.10058046
摘要
Abstract Data processing and storage in electronic devices are typically performed as a sequence of elementary binary operations. Alternative approaches, such as neuromorphic or reservoir computing, are rapidly gaining interest where data processing is relatively slow, but can be performed in a more comprehensive way or massively in parallel, like in neuronal circuits. Here, time-domain all-optical information processing capabilities of photon-avalanching (PA) nanoparticles at room temperature are discovered. Demonstrated functionality resembles properties found in neuronal synapses, such as: paired-pulse facilitation and short-term internal memory, in situ plasticity, multiple inputs processing, and all-or-nothing threshold response. The PA-memory-like behavior shows capability of machine-learning-algorithm-free feature extraction and further recognition of 2D patterns with simple 2 input artificial neural network. Additionally, high nonlinearity of luminescence intensity in response to photoexcitation mimics and enhances spike-timing-dependent plasticity that is coherent in nature with the way a sound source is localized in animal neuronal circuits. Not only are yet unexplored fundamental properties of photon-avalanche luminescence kinetics studied, but this approach, combined with recent achievements in photonics, light confinement and guiding, promises all-optical data processing, control, adaptive responsivity, and storage on photonic chips.
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