神经形态工程学
光子学
材料科学
Spike(软件开发)
光电子学
突触
计算机科学
高效能源利用
人工神经网络
电子工程
计算机体系结构
纳米技术
人工智能
电气工程
工程类
神经科学
生物
软件工程
作者
Semyon V. Bachinin,Maria Timofeeva,Alexandra Gavrilova,Svyatoslav A. Povarov,Vladimir Shirobokov,Alena N. Kulakova,Valentin A. Milichko
标识
DOI:10.1021/acsami.5c06829
摘要
The concept of photonic neuromorphic computing offers fast, energy-efficient, and autonomous data processing yet faces challenges in the design of an active material, enabling the desired performance. Here, we demonstrate a copper oxide microcrystal optical synapse, demonstrating efficient, fast, and highly enhanced photonic neuromorphic computing. By optically pumping a single microcrystal with 2.3 eV photons, we observe a history-dependent response of photoexcited electrons (spike), controlled by the pumping repetition rate. This neuromorphic behavior exhibits a 1 ms spike response time, a 102 on/off ratio, exceptional endurance over 13,400 cycles, and allows achieving 95% accuracy in handwritten digit recognition in three training epochs. The reported optical synapse surpasses most existing designs, paving the way for efficient and long-lasting photonic neuromorphic data processing.
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