Interleaved Diffractive Networks for Information Transfer Through Random Diffusers
Year: 2026
Type: article
Abstract: ABSTRACT Transferring optical information through random diffusers is a critical yet challenging task. Here, we introduce a cascaded diffractive optical network for information transfer through random and unknown diffusers, achieved through passive, structured layers physically interleaved within the scattering medium. These interleaved diffractive layers are optimized to mitigate the scattering process without requiring digital computing. The performance of this all‐optical system was quantified as a function of several physical parameters, including the diffractive processor's depth, the physical layout of the diffractive layers, and the statistical properties of the scattering medium. To further enhance the performance and robustness of information transfer through a scattering medium, we also developed a hybrid (optical‐digital) system that coupled the diffractive processor with a jointly trained digital neural network, which was shown to achieve superior reconstruction fidelity even when the input object information was subjected to unknown random rotations, shifts, and scaling. We also experimentally validated this system using a fabricated multi‐layer diffractive system in the visible spectrum, demonstrating reliable information recovery through random diffuser layers. Our numerical and experimental results demonstrate the capabilities of an interleaved diffractive processor to recover optical information through volumetric diffusive media, which can find applications in biomedical imaging, telecommunications, and remote sensing.
Source: Laser & Photonics Review
DOI: 10.1002/lpor.71471
Language: English
Subfield: Acoustics and Ultrasonics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,880
OpenAlex ID: W7166083078