论文标题
光子整合电路中的激光尖峰神经元
A Laser Spiking Neuron in a Photonic Integrated Circuit
论文作者
论文摘要
最近，人们对使用光子集成电路技术等线性操作（例如矩阵乘法）的实施引起了人们的兴趣。但是，这些方法需要一种在光子域中执行非线性操作的有效且灵活的方法。我们已经制造了一种光电非线性设备 - 一种激光神经元 - 它使用可兴奋的激光动力学来实现受生物学启发的尖峰行为。我们证明了跨多个波长的同时激发，抑制和求和的功能。我们还证明了与波长多路复用协议的层叠性和兼容性，这对于大规模系统集成至关重要。激光神经元是一类重要的光电非线性处理器，可以同时补充光子计算操作的巨大带宽密度和能源效率。
There has been a recent surge of interest in the implementation of linear operations such as matrix multipications using photonic integrated circuit technology. However, these approaches require an efficient and flexible way to perform nonlinear operations in the photonic domain. We have fabricated an optoelectronic nonlinear device--a laser neuron--that uses excitable laser dynamics to achieve biologically-inspired spiking behavior. We demonstrate functionality with simultaneous excitation, inhibition, and summation across multiple wavelengths. We also demonstrate cascadability and compatibility with a wavelength multiplexing protocol, both essential for larger scale system integration. Laser neurons represent an important class of optoelectronic nonlinear processors that can complement both the enormous bandwidth density and energy efficiency of photonic computing operations.
