Phys.org August 29, 2023
Free-space optical information transfer through diffusive media is critical in many applications but remains challenging due to random, unknown perturbations in the optical path. Researchers at UCLA demonstrated an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest through unknown random phase diffusers along the optical path. The model comprised a convolutional neural network-based electronic encoder and successive passive diffractive layers that were jointly optimized. After their joint training using deep learning, their hybrid model could transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers. The model was experimentally validated using a 3D-printed diffractive network carrying the desired optical information through random unknown diffusers. The framework could be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media… read more. Open Access TECHNICAL ARTICLEÂ
Pipeline of the hybrid electronic encoder and optical diffractive decoder… Credit: Advanced Photonics, Vol. 5, Issue 4, 046009 (August 2023)