NTT Basic Research Laboratories, NTT Corporation, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa, 243-0198, Japan.
Institute of Industrial Science, The University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo, 153-8505, Japan.
Nat Commun. 2021 Apr 23;12(1):2325. doi: 10.1038/s41467-021-22576-4.
Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective spiking dynamics of neurons, the fine control of spiking dynamics is desirable for neuromorphic devices. Here we show that photonic spiking neurons implemented with paired nonlinear optical oscillators can be controlled to generate two modes of bio-realistic spiking dynamics by changing optical-pump amplitude. When the photonic neurons are coupled in a network, the interaction between them induces an effective change in the pump amplitude depending on the order parameter that characterizes synchronization. The experimental results show that the effective change causes spontaneous modification of the spiking modes and firing rates of clustered neurons, and such collective dynamics can be utilized to realize efficient heuristics for solving NP-hard combinatorial optimization problems.
近年来，尖峰神经网络的非线性动力学作为一种理解大脑中可能的信息处理并将其应用于人工智能的方法引起了广泛关注。由于信息可以通过神经元的集体尖峰动力学来处理，因此对于神经形态设备来说，精细控制尖峰动力学是可取的。在这里，我们展示了通过改变光泵幅度，可以控制由成对非线性光学振荡器实现的光子尖峰神经元，以产生两种生物现实尖峰动力学模式。当光子神经元在网络中耦合时，它们之间的相互作用会根据特征同步的序参量引起泵幅度的有效变化。实验结果表明，这种有效变化导致簇状神经元的尖峰模式和发射率自发改变，并且这种集体动力学可用于实现解决 NP 难组合优化问题的有效启发式算法。
