Yu Sunkyu, Piao Xianji, Park Namkyoo
Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul 08826 Korea.
Adv Sci (Weinh). 2019 Jun 3;6(15):1900771. doi: 10.1002/advs.201900771. eCollection 2019 Aug 7.
As an elementary processor of neural networks, a neuron performs exotic dynamic functions, such as bifurcation, repetitive firing, and oscillation quenching. To achieve ultrafast neuromorphic signal processing, the realization of photonic equivalents to neuronal dynamic functions has attracted considerable attention. However, despite the nonconservative nature of neurons due to energy exchange between intra- and extra-cellular regions through ion channels, the critical role of non-Hermitian physics in the photonic analogy of a neuron has been neglected. Here, a neuromorphic non-Hermitian photonic system ruled by parity-time symmetry is presented. For a photonic platform that induces the competition between saturable gain and loss channels, dynamical phases are classified with respect to parity-time symmetry and stability. In each phase, unique oscillation quenching functions and nonreciprocal oscillations of light fields are revealed as photonic equivalents of neuronal dynamic functions. The proposed photonic system for neuronal functionalities will become a fundamental building block for light-based neural signal processing.
作为神经网络的基本处理器，神经元执行诸如分岔、重复放电和振荡猝灭等奇特的动态功能。为了实现超快速神经形态信号处理，实现与神经元动态功能等效的光子功能受到了广泛关注。然而，尽管由于离子通道导致细胞内和细胞外区域之间的能量交换，神经元具有非保守性质，但非厄米物理在神经元光子类比中的关键作用却被忽视了。在此，提出了一种由宇称-时间对称性支配的神经形态非厄米光子系统。对于一个诱导可饱和增益通道和损耗通道之间竞争的光子平台，根据宇称-时间对称性和稳定性对动态相进行分类。在每个相中，独特的振荡猝灭功能和光场的非互易振荡被揭示为神经元动态功能的光子等效物。所提出的用于神经元功能的光子系统将成为基于光的神经信号处理的基本构建模块。
