论文标题
光子尖峰神经元的集体和同步动力学
Collective and synchronous dynamics of photonic spiking neurons
论文作者
论文摘要
峰值神经网络的非线性动力学最近引起了人们极大的兴趣,是一种了解大脑中可能的信息处理并将其应用于人工智能的方法。由于可以通过神经元的集体尖峰动态来处理信息,因此对于神经形态设备而言,尖峰动力学的精细控制是可取的。在这里,我们表明,可以控制使用配对非线性光学振荡器实现的光子尖峰神经元通过更改光泵振幅来控制两种生物现实式尖峰动态模式。当它们在网络中耦合时,我们发现光子神经元之间的相互作用会导致泵振幅的有效变化,这取决于表征同步的顺序参数。实验结果表明,有效变化导致尖峰模式的自发修改和聚类神经元的点火速率,并且可以利用这种集体动力学来实现有效的启发式方法来解决NP-HARD组合优化问题。
Nonlinear dynamics of spiking neural networks has 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 the optical pump amplitude. When they are coupled in a network, we found that the interaction between the photonic neurons 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.