Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Optically Digitalized Holography: A Perspective for All-Optical Machine Learning

Holography, which was invented by Dennis Gabor in 1948, offers an approach to reconstructing both the amplitude and phase information of a three-dimensional (3D) object [1]. Since its invention, the concept of holography has been widely used in various fields, such as microscopy [2], interferometry [3], ultrasonography [4], and holographic display [5]. Optical holography can be divided into two steps: recording and reconstruction. A conventional hologram is recorded onto a photosensitive film as the interference between an object beam carrying the 3D object information and a reference beam. Thereafter, the original object wavefront is reconstructed in the 3D image space by illuminating the reference beam on the recorded hologram.

100 Hertz frame-rate switching threedimensional orbital angular momentum multiplexing holography via cross convolution

The orbital angular momentum(OAM)of light has been implemented as an information carrier in OAM holography.Holographic information can be multiplexed in theoretical unbounded OAM channels,promoting the applications of optically addressable dynamic display and high-security optical encryption.However,the frame-rate of the dynamic extraction of the information reconstruction process in OAM holography is physically determined by the switching speed of the incident OAM states,which is currently below 30 Hz limited by refreshing rate of the phase-modulation spatial light modulator(SLM).Here,based on a cross convolution with the spatial frequency of the OAM-multiplexing hologram,the spatial frequencies of an elaborately-designed amplitude distribution,namely amplitude decoding key,has been adopted for the extraction of three-dimensional holographic information encoded in a specific OAM information channel.We experimentally demonstrated a dynamic extraction frame rate of 100 Hz from an OAM multiplexing hologram with 10 information channels indicated by individual OAM values from-50 to 50.The new concept of cross convolution theorem can even provide the potential of parallel reproduction and distribution of information encoded in many OAM channels at various positions which boosts the capacity of information processing far beyond the traditional decoding methods.Thus,our results provide a holographic paradigm for high-speed 3D information processing,paving an unprecedented way to achieve the high-capacity short-range optical communication system.

Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed,ultrawide bandwidths and low energy consumption because the optical dimensions(time,space,wavelength,and polarization)could be utilized to increase the degree of freedom.However,due to the lack of the capability to extract the information features in the orbital angular momentum(OAM)domain,the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model.Here,we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network(CNN)based on Laguerre-Gaussian(LG)beam modes with diverse diffraction losses.The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction,and deep-learning diffractive layers as a classifier.The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding,leading to an accuracy as high as 97.2%for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes,as well as a resistance to eavesdropping in point-to-point free-space transmission.Moreover,through extending the target encoded modes into multiplexed OAM states,we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%.Our work provides a deep insight to the mechanism of machine learning with spatial modes basis,which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

High-dimensional orbital angular momentum multiplexing nonlinear holography

Nonlinear holography has been identified as a vital platform for optical multiplexing holography because of the appearance of new optical frequencies.However,due to nonlinear wave coupling in nonlinear optical processes,the nonlinear harmonic field is coupled with the input field,laying a fundamental barrier to independent control of the interacting fields for holography.We propose and experimentally demonstrate high-dimensional orbital angular momentum(OAM)multiplexing nonlinear holography to overcome this problem.By dividing the wavefront of the fundamental wave into different orthogonal OAM channels,multiple OAM and polarization-dependent holographic images in both the fundamental wave and second-harmonic wave have been reconstructed independently in the spatial frequency domain through a type-II second harmonic generation process.Moreover,this method can be easily extended to cascadedχ2 nonlinear optical processes for multiplexing in more wavelength channels,leading to potential applications in multicasting in optical communications,multiwavelength display,multidimensional optical storage,anticounterfeiting,and optical encryption.