Holographic imaging poses significant challenges when facing real-time disturbances introduced by dynamic environments. The existing deep-learning methods for holographic imaging often depend solely on the specific condition based on the given data distributions, thus hindering their generalization across multiple scenes. One critical problem is how to guarantee the alignment between any given downstream tasks and pretrained models. We analyze the physical mechanism of image degradation caused by turbulence and innovatively propose a swin transformer-based method, termed train-with-coherence-swin (TWC-Swin) transformer, which uses spatial coherence (SC) as an adaptable physical prior information to precisely align image restoration tasks in the arbitrary turbulent scene. The light-processing system (LPR) we designed enables manipulation of SC and simulation of any turbulence. Qualitative and quantitative evaluations demonstrate that the TWC-Swin method presents superiority over traditional convolution frameworks and realizes image restoration under various turbulences, which suggests its robustness, powerful generalization capabilities, and adaptability to unknown environments. Our research reveals the significance of physical prior information in the optical intersection and provides an effective solution for model-to-tasks alignment schemes, which will help to unlock the full potential of deep learning for all-weather optical imaging across terrestrial, marine, and aerial domains.

Optical geometrical transformation is a novel and powerful tool to switch orbital angular momentum (OAM) states in modern optics. We demonstrate a scheme to operate multiplication and division in OAM by Fermat’s spiral transformation. The characteristics of the output beams in the case of integer and fraction OAM operations are presented in detail. Additionally, the power weight of the output OAM modes and the interference patterns of the output beams are reported to confirm the expected ability of OAM mode conversion by Fermat’s spiral transformation. We further investigate the evolution of OAM beams in operations theoretically and experimentally. This work provides a practical way to perform an optical transformation mapping on OAM beams. It can find application in optical communications with larger OAM mode numbers as well as quantum information in high-dimensional systems.

We introduce a new class of partially coherent asymmetric array beams. When the beam propagates, the spectral density of each lobe and the corresponding degree of coherence have rotating behavior. Especially, not only can array-like lattices revolve arbitrarily, but also they can move freely by controlling transverse plane shifts. Furthermore, we have generated this kind of beam experimentally, and the experimental phenomena are consistent with the numerical simulation results. Such a rotating beam with free movement and revolution may broaden the way for optical applications. More importantly, it inspires further studies in the field of asymmetric coherence gratings and lattices.

The far-zone scattered spectral density of a light wave on the scattering from a collection of particles is investigated, and the relationship between the character of the collection and the distribution of the scattered spectral density is discussed. It is shown that both the number of particles and their locations in the collection play roles in the distribution of the far-zone scattered spectral density. This phenomenon may provide a potential method to reconstruct the structure character of a collection of particles from measurements of the far-zone scattered spectral density.