Performing optical logic operations by a diffractive neural network.,Light: Science & Applications

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Performing optical logic operations by a diffractive neural network.
Light: Science & Applications ( IF 20.6 ) Pub Date : 2020-04-13 , DOI: 10.1038/s41377-020-0303-2
Chao Qian _{1,

2,

3,

4} , Xiao Lin _{1,

5} , Xiaobin Lin ₁ , Jian Xu ₃ , Yang Sun _{1,

2} , Erping Li _{1,

4} , Baile Zhang ₅ , Hongsheng Chen _{1,

2,

4}

Affiliation

Optical logic operations lie at the heart of optical computing, and they enable many applications such as ultrahigh-speed information processing. However, the reported optical logic gates rely heavily on the precise control of input light signals, including their phase difference, polarization, and intensity and the size of the incident beams. Due to the complexity and difficulty in these precise controls, the two output optical logic states may suffer from an inherent instability and a low contrast ratio of intensity. Moreover, the miniaturization of optical logic gates becomes difficult if the extra bulky apparatus for these controls is considered. As such, it is desirable to get rid of these complicated controls and to achieve full logic functionality in a compact photonic system. Such a goal remains challenging. Here, we introduce a simple yet universal design strategy, capable of using plane waves as the incident signal, to perform optical logic operations via a diffractive neural network. Physically, the incident plane wave is first spatially encoded by a specific logic operation at the input layer and further decoded through the hidden layers, namely, a compound Huygens' metasurface. That is, the judiciously designed metasurface scatters the encoded light into one of two small designated areas at the output layer, which provides the information of output logic states. Importantly, after training of the diffractive neural network, all seven basic types of optical logic operations can be realized by the same metasurface. As a conceptual illustration, three logic operations (NOT, OR, and AND) are experimentally demonstrated at microwave frequencies.

中文翻译：

通过衍射神经网络执行光学逻辑运算。

光学逻辑运算是光学计算的核心，它们使许多应用成为可能，例如超高速信息处理。然而，所报道的光学逻辑门在很大程度上依赖于对输入光信号的精确控制，包括它们的相位差，偏振，强度和入射光束的大小。由于这些精确控制的复杂性和困难性，两个输出光学逻辑状态可能会遭受固有的不稳定性和强度的低对比度。此外，如果考虑到用于这些控制的额外庞大的设备，则光学逻辑门的小型化将变得困难。因此，希望摆脱这些复杂的控制并在紧凑的光子系统中实现完整的逻辑功能。这样的目标仍然具有挑战性。这里，我们介绍了一种简单而通用的设计策略，该策略能够使用平面波作为入射信号，通过衍射神经网络执行光学逻辑运算。在物理上，入射平面波首先在输入层通过特定的逻辑运算在空间上进行编码，然后再通过隐藏层（即复合惠更斯的超表面）进行解码。也就是说，经过精心设计的超颖表面将编码的光散射到输出层的两个小指定区域之一，从而提供了输出逻辑状态的信息。重要的是，在训练了衍射神经网络之后，所有七个基本类型的光学逻辑运算都可以通过同一超颖表面实现。作为概念说明，在微波频率上通过实验证明了三种逻辑运算（NOT，OR和AND）。

更新日期：2020-04-24

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