神经形态工程学
光子学
双功能
计算机科学
人工神经网络
突触
可扩展性
人工智能
可塑性
纳米技术
计算机体系结构
突触可塑性
材料科学
神经科学
变质塑性
功能(生物学)
分拆(数论)
神经系统
物理
工程类
电子工程
光开关
机制(生物学)
超短脉冲
作者
Yanbing Han,Junhao Zhu,Shiyu Zhu,Han Gao,Zhe Ma,Mochen JIA,Xu Chen,JiBin ZHANG,Linyuan Lian,Ying Liu,Dongwen Yang,Junlu Sun,Lu Dong,Zhifeng SHI
标识
DOI:10.1002/lpor.202503062
摘要
ABSTRACT Advances in artificial synaptic devices are indispensable for deepening the physical underpinnings of neural networks and for diversifying the tasks that artificial intelligence can tackle. Yet, the photonic synapses demonstrated so far mostly demand electrical readout or intricate heterostructures, and none has offered a built‐in, material‐level mechanism that unites short‐term plasticity with long‐term memory in a monolayer, all‐optical platform. We introduce Ti‐doped CaSb 2 O 6 as a purely photonic synapse whose bifunctional shallow and deep traps natively partition volatile and non‐volatile memory. Dual‐wavelength UV control (275 nm excitation/365 nm inhibition) elicits short‐term facilitation, spike‐number‐dependent potentiation, post‐tetanic potentiation, and erasable storage. From these dynamics we derive an “Opto‐Logistic” activation function and embed it in a lightweight neural network hosted on a microcontroller, demonstrating an AI “dog” that autonomously classifies vegetables and can be retrained for new categories like fruits within a reservoir‐computing framework. The findings reveal how persistent luminescence can mirror biological synaptic physics and furnish both material and system‐level design rules for scalable photonic neuromorphic processors.
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