Introduction and Outline

High-performance material plays a crucial role in holographic data storage, which is a noteworthy technology with potential applications in the field of high capacity data storage. We report on a new kind of holographic storage material based on aluminum nanoparticles (Al NPs) dispersed phenanthrenequinone-doped poly(methyl methacrylate) (PQ/PMMA) photopolymer. Al NPs are efficiently synthesized in a monomer solvent using laser ablation in liquids without chemical precursors. It is shown that an increase in diffraction efficiency and recording sensitivity is achieved in both traditional holography and polarization holography by doping with Al NPs. After 4 h of ablation, the new material exhibited an improvement in the diffraction efficiency for both traditional holography and polarization holography from 2.85% to 57.15% and from 0.6% to 4.07%, respectively. We also investigated the image recording and reconstruction performance for both traditional and polarization holography and the results indicate that the proposed material has noticeable potential as a holographic storage material. Additionally, it also possesses excellent potential for holographic position multiplexing recording. We conclude that laser ablation in a liquid is a promising option for processing low-cost nano-doped holographic storage material.

Liquid crystal spatial light modulators for precise dynamic manipulation of coherent light fields, used in diffractive optoelectronic optical data processing systems, are considered. This paper presents the results of a study of the temporal dynamics of the HoloEye PLUTO-2 VIS-016 liquid crystal spatial light modulator for analysis of light fields rate modulation. Experiments using binary phase computer generated holograms and binary focusing phase diffractive optical elements were conducted. Based on experimental data, the time characteristics of the modulator response were determined. It was found that when the rise time of the diffraction efficiency was 146 ms after the hologram displaying onto the SLM, and when switching to a new hologram, the decay time was 97 ms. These results allowed the dynamic generation of an alternating holograms at a refresh rate of 2 Hz with an interference level of –16 dB. Increasing the frequency of fringe pattern updates increases the level of interframe noise in the generated holograms, and when updated at the specification frequency, the generated distributions cannot be separated. Determining the actual frame rate based on the rise and decay times of the diffraction efficiency makes it possible to correctly calculate the minimum operating time of an information optical system containing a liquid crystal spatial light modulator.

Vector orbital angular momentum (OAM) beams, described by higher-order Poincaré (HOP) sphere, are generalized forms of waves carrying OAM with an inhomogeneous polarization of wavefronts. We construct all-dielectric metasurfaces with adjustable amplitude, polarization, and phase to generate arbitrary vector OAM beams. The metasurface is composed of two pairs of silicon nanopillars arranged alternately. Using the interference effect of the four meta-atoms related to the circular polarization, combined with the propagation and geometric phases, two OAM beams with controlled amplitude, phase, and equal topological charge but opposite signs can be obtained under the incidence of orthogonally circularly polarized lights. For the x linearly polarized light, arbitrary vector OAM beams on the HOP sphere are generated via the superposition of the above OAM beams. Additionally, the evolution process of the beam on the longitude and latitude of the Poincaré sphere is revealed by changing the amplitude and phase of the two OAM beams. This work provides a simple, effective, and flexible method for realizing vector OAM beams while having potential implications for the generation and manipulation of vectorial light fields at the micro-nano scale.

The characteristics of holographic recording in the presence of phase noise caused by air disturbances and by vibrations were studied. Diffraction efficiencies were calculated using the finite-difference time-domain method. The simulation results show that the amplitudes of fringes decreases with increasing phase noise, and thus diffraction efficiencies decrease. A novel method of phase compensation for holographic data storage is proposed. Interference fringes are incident on a charge coupled device (CCD) camera symmetrically positioned in relation to the recording media, and the fringes in the media are estimated using the fringes monitored by the camera. The phase information is calculated using a fast Fourier transform, and a phase modulator is set in the reference beam's path and driven to reduce the phase error, so that the phase at the CCD camera is stabilized. With this method, the standard deviation of the phase error is decreased to less than 1/10^th that of the conventional method. The diffraction efficiencies of angle multiplex recording using photopolymer were measured. The diffraction efficiency with phase compensation at 0 degree was 700% larger than without it, and the total relative multiplexing number improved by 50%. When digital data are recorded, we found that the histogram distribution of the symbol "1" (a white signal) was a Gaussian density and the distribution of the symbol "0" (a black signal) was a Rayleigh density. We also proposed a novel SNR measure suitable for holographic data storage. When this phase compensation method was applied to digital holographic storage in which a spatial light modulator (SLM) was set on reference beam's path, a 5.0-dB improvement in SNR compared with the value without phase compensation was obtained. As holographic data storage can record phase, the proposed method can be made into a feasible technology.

In this paper, an aberration correction method for an extended target is proposed to solve the problem of the lenslet-based plenoptic camera not imaging clearly under the influence of aberrations. We propose a light field manipulation method to improve performance of the light field imaging system. The principle of this method is that the sub-aperture images extracted from the raw light field image are offset when the light field imaging system is affected by aberrations, and the symmetrical arrangement of the sub-aperture image array is destroyed. By repairing the symmetrical arrangement of the sub-aperture image array, the influence of phase aberrations on the imaging system can be eliminated, and the resolution of the plenoptic camera can be improved. We use an image correlation algorithm to process the sub-aperture images of the plenoptic camera, calculate and compensate each sub-aperture image's displacement caused by aberrations, and restore the symmetrical arrangement of the sub-aperture image array; then, a corrected high-resolution refocused image can be generated. In particular, this method uses only the raw light field information obtained by the plenoptic camera in a single exposure, without adding other hardware devices. Furthermore, it takes the extended target itself as the reference image, so the ideal position need not be calibrated in advance. Also, the parallax information of the sub-aperture images is retained, and the method is simple and easy to use. Numerical simulation and experimental results show that the technology proposed in this paper can work well for high-resolution imaging of a plenoptic camera with phase aberrations. This method can be potentially applied to analyze lens aberration, media-induced image distortion such as water turbulence in underwater imaging, and atmospheric turbulence in remote imaging. It may have important application prospects in the fields of astronomical object detection, remote sensing, etc.

Conventional spectral image demosaicing algorithms rely on pixels' spatial or spectral correlations for reconstruction. Due to the missing data in the multispectral filter array (MSFA), the estimation of spatial or spectral correlations is inaccurate, leading to poor reconstruction results, and these algorithms are time-consuming. Deep learning-based spectral image demosaicing methods directly learn the nonlinear mapping relationship between 2D spectral mosaic images and 3D multispectral images. However, these learning-based methods focused only on learning the mapping relationship in the spatial domain, but neglected valuable image information in the frequency domain, resulting in limited reconstruction quality. To address the above issues, this paper proposes a novel lightweight spectral image demosaicing method based on joint spatial and frequency domain information learning. First, a novel parameter-free spectral image initialization strategy based on the Fourier transform is proposed, which leads to better initialized spectral images and eases the difficulty of subsequent spectral image reconstruction. Furthermore, an efficient spatial-frequency transformer network is proposed, which jointly learns the spatial correlations and the frequency domain characteristics. Compared to existing learning-based spectral image demosaicing methods, the proposed method significantly reduces the number of model parameters and computational complexity. Extensive experiments on simulated and real-world data show that the proposed method notably outperforms existing spectral image demosaicing methods.

Topological light fields represent a cutting-edge frontier at the intersection of modern optics and condensed matter physics, offering new dimensions for light field control and functional expansion through their distinctive topological structures. This review traces the progression from singular optics to optical skyrmions, providing an overview of representative real-space topological features, including phase singularities, polarization singularities, optical knots, and Möbius strips. It focuses on the generation mechanisms and characterization techniques of various types of optical skyrmions in parameter space, and reviews key studies that have shaped the development of the field. With ongoing advances in nano-optics and light-field manipulation, topological light fields exhibit strong potential in high-dimensional optical communication, massive data storage, all-optical computing, and precision metrology. This review aims to offer a coherent framework for researchers in topological optics and to support the further exploration of topological structures in optical devices and photonic information technologies.

We present single-shot fast phase information retrieval without interferometry in the holographic data storage. Noninterferometry systems are more compact and stable than interferometric ones. Only single-shot of the intensity distribution on the Fourier plane is required to retrieve the phase information. Enhanced iterative Fourier transform algorithm (IFTA) was developed by applying embedded known phase data and phase only modulation as the prior constraints, which can be provided easily as the code rule in holographic data storage system. Strong intensity distribution on the Fourier plane reduces the requirement of high-power laser and high material diffractive efficiency. The bit-errorrate (BER) can be decreased to 0 in the simulation study. We realized BER without check code in the order of 10-2 for 4 level phase retrieval experimentally. The code rate is increased by 2.8 times using 4 level phase code compared to with amplitude code.

The higher-order Hermite–Gaussian (HG) modes exhibit complex spatial distributions and find a wide range of applications in fields such as quantum information processing, optical communications, and precision measurements. In recent years, the advancement of deep learning has emerged as an effective approach for generating higher-order HG modes. However, the traditional data-driven deep learning method necessitates a substantial amount of labeled data for training, entails a lengthy data acquisition process, and imposes stringent requirements on system stability. In practical applications, these methods are confronted with challenges such as the high cost of data labeling. This paper proposes a method that integrates a physical model with deep learning. By utilizing only a single intensity distribution of the target optical field and incorporating the physical model, the training of the neural network can be accomplished, thereby eliminating the dependency of traditional data-driven deep learning methods on large datasets. Experimental results demonstrate that, compared with the traditional data-driven deep learning method, the method proposed in this paper yields a smaller root mean squared error between the generated higher-order HG modes. The quality of the generated modes is higher, while the training time of the neural network is shorter, indicating greater efficiency. By incorporating the physical model into deep learning, this approach overcomes the limitations of traditional deep learning methods, offering a novel solution for applying deep learning in light field manipulation, quantum physics, and other related fields.

Photonic Radial Modes: Progress in Light Field Manipulation and Quantum Information Applications

After years of development, holography has become an essential tool of modern optics for many applications. Among them, holographic encryption and dynamic display are the two most typical applications. So far, however, only 2D targets or 2D images of 3D targets can be encrypted with holographic technology. The 3D multiplexing holographic technology of 3D multi‐targets has not yet been realized and holographic encryption of 3D multi‐targets is still a blank. Here, the conception of 3D orbital angular momentum (OAM) multiplexing holography is proposed, and holographic encryption of 3D multi‐targets is realized for the first time. This breaks the restriction that only 2D images can be encrypted in traditional holographic encryption. Furthermore, the results also show that the 3D OAM holography can be used in the dynamic display for 3D multi‐targets. In the experiment, the metasurface is used for taking its high‐resolution advantage in light field manipulation, and verify the feasibility of 3D OAM multiplexing holographic technology, holographic encryption of 3D multi‐targets, and holographic dynamic display of 3D targets. The work creates a precedent for the 3D multiplexing holography, encryption, and dynamic display technology of 3D multi‐targets, which brings real 3D life closer to humankind.

The inertial measurement system based on the SERF effect utilizes the rotation of the inertia-sensitive space with longitudinally hyperpolarized nuclear spin, possessing the potential for ultra-high sensitivity measurement, and has become an important development direction for the high-sensitivity miniaturized inertial navigation systems. The polarization distribution uniformity in the atomic spin ensemble significantly influences the scale factor error and bias stability of the SERF inertial measurement system. This paper analyses the factors affecting the longitudinal and transverse polarization distribution in the atomic spin coupled ensemble of the SERF inertial measurement system. To address the issue of non-uniform polarization rate distribution in the electron spin-nuclear spin coupled ensemble, a Bloch differential equation model is established. Using light field manipulation techniques, three-dimensional polarization rate distribution of the atomic spin ensemble under Gaussian, flat-top, and hollow beam pumping are simulated. Relevant simulation parameters are optimized, with over 80% of the normalized nuclear spin polarization rate considered as the uniform region. Under hollow beam pumping, the transverse nuclear spin polarization uniformity is improved by 88.3% compared to Gaussian beams and by 20.9% compared to flat-top beams, providing a theoretical basis for further enhancing the polarization uniformity in the atomic spin coupled ensemble.

Phase retrieval in holographic data storage by expanded spectrum combined with dynamic sampling method is proposed, which serves to both reduce media consumption and to shorten the iterative number of phase code retrieval. Generally, high-fidelity phase retrieval requires twice Nyquist frequency in phase-modulated holographic data storage. To increase storage density, we only recorded and captured the signal with Nyquist size and used the frequency expanded method to realize high-fidelity phase retrieval. In the decoding process, the iterative Fourier transform algorithm is used to retrieve the phase information of the reconstructed beam. The expanded spectrum is dynamically sampled, which can provide a faster convergence path for the phase retrieval. We aimed to demonstrate the possibility of integrating various methods on the Fourier domain and providing a potential way to improve the performance of holographic data storage systems. The simulation and experimental results proved the combination of processing methods in frequency spectrum was benefit.

Light field (LF) imaging has gained significant attention due to its recent success in microscopy, 3-dimensional (3D) displaying and rendering, augmented and virtual reality usage. Postprocessing of LF enables us to extract more information from a scene compared to traditional cameras. However, the use of LF is still a research novelty because of the current limitations in capturing high-resolution LF in all of its four dimensions. While researchers are actively improving methods of capturing high-resolution LF's, using simulation, it is possible to explore a high-quality captured LF's properties. The immediate concerns following the LF capture are its storage and processing time. A rich LF occupies a large chunk of memory ---order of multiple gigabytes per LF---. Also, most feature extraction techniques associated with LF postprocessing involve multi-dimensional integration that requires access to the whole LF and is usually time-consuming. Recent advancements in computer processing units made it possible to simulate realistic images using physical-based rendering software. In this work, at first, a transformation function is proposed for building a camera array (CA) to capture the same portion of LF from a scene that a standard plenoptic camera (SPC) can acquire. Using this transformation, LF simulation with similar properties as a plenoptic camera will become trivial in any rendering software. Artificial intelligence (AI) and machine learning (ML) algorithms ---when deployed on the new generation of GPUs--- are faster than ever. It is possible to generate and train large networks with millions of trainable parameters to learn very complex features. Here, residual convolutional neural network (RCNN) structures are employed to build complex networks for compression and feature extraction from an LF. By combining state-of-the-art image compression and RCNN, I have created a compression pipeline. The proposed pipeline's bit per pixel (bpp) ratio is 0.0047 on average. I show that with a 1% compression time cost and 18x speedup for decompression, our methods reconstructed LFs have better structural similarity index metric (SSIM) and comparable peak signal-to-noise ratio (PSNR) compared to the state-of-the-art video compression techniques used to compress LFs. In the end, using RCNN, I created a network called RefNet, for extracting a group of 16 refocused images from a raw LF. The training parameters of the 16 LFs are set to (\alpha=0.125, 0.250, 0.375, ..., 2.0) for training. I show that RefNet is 134x faster than the state-of-the-art refocusing technique. The RefNet is also superior in color prediction compared to the state-of-the-art

The present theory underlying the concept of the modulation transfer function of magnification radiography MTFm, although mathematically consistent, raises fundamental questions in the practical application. It has not been demonstrated that, for objects of finite thickness, the exposing operation is a linear and isoplanatic process which can be described by a convolution integral in the spatial domain and a multiplication in the spatial frequency domain. In other words, it needs to be shown that OTFm satisfies the relation Sout( nu )=OTFm( nu )Sin( nu ) where OTFm( nu ) is the optical transfer function of magnification radiography, and Sin( nu ) and Sout( nu ) are the input and output Fourier spectra of an object, respectively. It is difficult to verify this relationship experimentally by means of ordinary diagnostic equipment, since important physical parameters, such as focal spot size, cannot be measured accurately. Therefore, experiments have been performed using a blood vessel phantom and a focal spot simulated by an 241Am source and a small lead aperture. From a comparison of theoretical and experimental data, it can be concluded that OTFm, and therefore also MTFm, are indeed transfer functions in the sense of the above equation.