Diffractive deep neural networks (D2NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational tasks between an input and output field-of-view (FOV). Here, we present a pyramid-structured diffractive optical network design (which we term P-D2NN), optimized specifically for unidirectional image magnification and demagnification. In this design, the diffractive layers are pyramidally scaled in alignment with the direction of the image magnification or demagnification. This P-D2NN design creates high-fidelity magnified or demagnified images in only one direction, while inhibiting the image formation in the opposite direction - achieving the desired unidirectional imaging operation using a much smaller number of diffractive degrees of freedom within the optical processor volume. Furthermore, P-D2NN design maintains its unidirectional image magnification/demagnification functionality across a large band of illumination wavelengths despite being trained with a single wavelength. We also designed a wavelength-multiplexed P-D2NN, where a unidirectional magnifier and a unidirectional demagnifier operate simultaneously in opposite directions, at two distinct illumination wavelengths. Furthermore, we demonstrate that by cascading multiple unidirectional P-D2NN modules, we can achieve higher magnification factors. The efficacy of the P-D2NN architecture was also validated experimentally using terahertz illumination, successfully matching our numerical simulations. P-D2NN offers a physics-inspired strategy for designing task-specific visual processors.

翻译：衍射深度神经网络由一系列透射层构成，这些层通过监督式深度学习进行优化，可在输入与输出视场之间全光学地执行各类计算任务。本文提出一种金字塔结构的衍射光学网络设计（称为P-D2NN），专门针对单向图像放大与缩小任务进行优化。在该设计中，衍射层沿图像放大或缩小的方向按金字塔结构进行尺度缩放。这种P-D2NN设计仅沿单一方向生成高保真度的放大或缩小图像，同时抑制反向的图像形成——在光学处理器体积内使用更少的衍射自由度即可实现所需的单向成像操作。此外，尽管仅使用单一波长进行训练，P-D2NN设计仍能在宽波段照明波长范围内保持其单向图像放大/缩小功能。我们还设计了波长复用型P-D2NN，其中单向放大器和单向缩小器可在两个不同照明波长下沿相反方向同时工作。进一步研究表明，通过级联多个单向P-D2NN模块，可以实现更高的放大倍数。P-D2NN架构的有效性已通过太赫兹照明实验得到验证，实验结果与数值模拟高度吻合。P-D2NN为设计任务专用视觉处理器提供了一种基于物理原理的创新策略。