Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with various applications ranging from imaging to beam focusing. Here, we present the design of a diffractive wavefront processor to approximate all-optical phase conjugation operation for input fields with phase aberrations. Leveraging deep learning, a set of passive diffractive layers was optimized to all-optically process an arbitrary phase-aberrated coherent field from an input aperture, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated the efficacy of this wavefront processor by 3D fabricating diffractive layers trained using deep learning and performing OPC on phase distortions never seen by the diffractive processor during its training. Employing terahertz radiation, our physical diffractive processor successfully performed the OPC task through a shallow spatially-engineered volume that axially spans tens of wavelengths. In addition to this transmissive OPC configuration, we also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and scalable nature, our diffractive wavefront processor can be used for diverse OPC-related applications, e.g., turbidity suppression and aberration correction, and is also adaptable to different parts of the electromagnetic spectrum, especially those where cost-effective wavefront engineering solutions do not exist.

翻译：光学相位共轭（OPC）是一种用于抵消波前畸变的非线性技术，在成像、光束聚焦等领域具有广泛应用。本文提出了一种基于衍射波前处理器（diffractive wavefront processor）的设计，用于近似的全光相位共轭操作，可处理存在相位像差的输入场。通过深度学习技术，我们优化了一组无源衍射层，使其能够以全光学方式任意处理来自输入孔径的相位畸变相干场，并产生输出场，其相位分布为输入波的共轭。我们通过三维打印经深度学习训练的衍射层，并针对训练过程中从未遇到的相位畸变执行OPC，实验验证了该波前处理器的有效性。利用太赫兹辐射，我们的物理衍射处理器成功通过轴向跨度仅数十波长的浅层空间工程化体积完成了OPC任务。除透射式OPC配置外，我们还通过将深度学习优化的衍射层与标准反射镜结合，构建了衍射式相位共轭镜。由于其紧凑、无源及可扩展的特性，该衍射波前处理器可广泛应用于与OPC相关的场景（如浑浊介质抑制和像差校正），并适用于电磁波谱的不同波段，尤其适用于缺乏高性价比波前工程解决方案的频段。