  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.
