集成光子神经网络中基于硅微环谐振器的非线性激活函数生成

Mircea Catuneanu, R. Hamerly, Nirav Annavarapu, Shahryar Sabouri, K. Jamshidi
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引用次数: 5

摘要

为了克服CMOS神经网络(NN)实现的互连问题(在抑制速度的同时增加功耗),已经提出了基于小规模线性光学的解决方案来取代多个工作中的电子神经网络层,例如[1-3]。然而,全光神经网络很难实现,因为它意味着取代现有的电光信号转换和数字驱动的神经网络层之间的激活函数。在这项工作中,我们展示了如何将反馈控制的微环谐振器(MRR)用作神经网络中的激活函数。我们关注的设计如图1-a所示。不同频率的光脉冲携带信号,权值使用适当自由频谱范围的PIN环调制器施加。脉冲用于确保由于设备加热而引起的失谐在很大程度上被避免。然后,光在负责非线性传递函数的主环形谐振器中耦合。功率依赖响应由自由载流子色散和自由载流子吸收之间的相互作用决定[4]。电子反馈回路将确保载波寿命控制,这对输出稳定性和再现性至关重要。然后,该谐振器的输出再次过滤以提取必要的信号,然后将其传递到下一个神经网络层。
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Nonlinear Activation Function Generation Based on Silicon Microring Resonators for Integrated Photonic Neural Networks
To overcome the interconnect problem of CMOS Neural Network (NN) implementations (increased power consumption while inhibiting speed), small-scale linear optics-based solutions have been proposed to replace the electronic NN layer in multiple works — e.g. [1–3]. Nevertheless, an all-optical NN is difficult to achieve as it would imply substituting the existing electro-optic signal conversion and digital-driven activation function necessary between NN layers. In this work, we demonstrate how feedback controlled microring resonators (MRR) can be used as activation functions in NNs. The design we focus on is shown in Fig. 1-a. Pulses of light at different frequencies carry signals while weights are applied using PIN ring modulators with proper free spectral range. Pulses are used to ensure that the detuning due to heating of the device is mostly avoided. The light is then coupled in the main ring resonator responsible for the non-linear transfer function. The power dependent response is governed by an interplay between free carrier dispersion and free carrier absorption [4]. An electronic feedback loop will ensure carrier lifetime control, crucial for output stability and reproducibility. The output of this resonator is then filtered again to extract the necessary signal, before passing it to the next NN layer.
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