The modulation of light is important in phase holographic data storage, and different spatial light modulators have different modulation capabilities for light. In this study, a lens less non-interference phase reconstruction system based on deep learning is applied to evaluate the performance differences of different spatial light modulators in holographic data storage. The performance differences are evaluated, which include the deep learning results versus pixel crosstalk results for phased holographic optical storage.
KEYWORDS: Bragg cells, High speed cameras, Digital micromirror devices, Holography, Data storage, Cameras, Holographic data storage systems, Signal generators, Imaging systems, Digital recording
The frame frequency matching of the Digital Micro-mirror Device (DMD), the acousto-optic modulator (AOM) and high-speed camera can realize the holographic high-speed reading under the reference light changing scene, which greatly improves the data reading speed. In this work, the frame frequency matching to achieve high-speed reading is related to four factors: the resolution and exposure time of the high-speed camera, the duty ratio of AOM, and the phase difference between the signals sent by AOM and DMD. Through the research of the exposure time and resolution of high-speed cameras, the maximum synchronous frame rate of DMD and high-speed cameras can achieve 18KHZ. By synchronizing the frame frequency of both DMD and AOM trigger signals with the signal generator, controlling the duty ratio of AOM and the phase difference of the trigger signals sent to DMD and AOM can enable the high-speed camera to read the reproduction data page near the data recording point, avoiding the waste of storage space. The analysis of the experimental results shows that the camera can read clear information under the conditions of the incident optical power density is 32μw, the AOM duty ratio is larger than 10%, and the phase difference between AOM and DMD is 26°. The realization of DMD, high-speed camera and AOM frequency matching will effectively ensure the reading speed and decoding accuracy of holographic stored data
KEYWORDS: Phase reconstruction, Holography, Data storage, Image processing, Phase shift keying, Image compression, Diffraction, Deep learning, Photonics, Education and training
Holographic data storage systems are candidates for information recording due to their large storage capacity and high transmission rate. In this paper, a phase modulation holographic storage technology with three-grayscale encoding is proposed and implemented. According to the experimental results, if two phase codes in the three-grayscale encoding are relatively close, the performance of phase reconstruction would be degenerated.
Displacement multiplexing can improve the storage density of collinear holographic data storage systems and is an essential multiplexing method. This article introduces the use of dark reaction phenomena in recording media to improve the displacement multiplexing effect of collinear holographic data storage systems, and achieves a multiplexing distance of 5 μm.
Research is to further increase the display size of the original 3D display system to achieve a better display effect. In order to achieve our goal, we adopted a new method to achieve large-area rotation display and at the same time reduce the noise generated by rotating parts during high-speed rotation. In this study, the relevant technology of magnetic levitation bearing is used for reference[1] and the magnetic bearing is mainly used to offset the gravity of the intermediate turntable and reduce the noise generated by friction and the brushless motor is used to improve the speed of the turntable, hoping to obtain better imaging effect. At the same time, high-precision sensors are used to read the rotation speed and rotation Angle of the magnetic levitation bearing.
Exposure intensity affects the diffraction intensity and bit error rate of holographic materials. Now we design the experiment, unify the exposure amount, adjust the intensity of the information light and the recording time, and observe the bit error rate and diffraction intensity after the dark reaction for 1 minute. We verify that holograms with high intensity and short exposure time and dark reaction after 1 minute have lower bit error rate and higher diffraction intensity
KEYWORDS: Data storage, Holography, Deep learning, Tunable filters, Phase retrieval, Education and training, Optical filters, Linear filtering, Data modeling, Signal to noise ratio
Holographic data storage is a powerful potential technology to solve the problem of mass data long-term storage. To increase the storage capacity, the information to be stored is encoded into a complex amplitude. Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout. In this talk, we propose a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase. By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages, the inverse problem is decomposed into two backward operators denoted by two convolutional neural networks to demodulate amplitude and phase respectively. The stable and simple complex amplitude demodulation and strong anti-noise performance from the deep learning provide an important guarantee for the practicality of holographic data storage.
KEYWORDS: Deep learning, Crosstalk, Spatial light modulators, Phase retrieval, Phase reconstruction, Diffraction, Data storage, Near field diffraction, Image restoration, Photonics
In the holographic data storage system, we can use deep learning method to learn the relationship between phase patterns and their near-field diffraction intensity images. In the practice, pixel crosstalk always exists. We found the pixel crosstalk between adjacent variable phase pixels was benefit for quick and accurate phase retrieval based on deep learning. We validated our idea by the simulation of adding phase disturbance between pixels on the spatial light modulator.
Compared with traditional iterative methods, deep learning phase reconstruction has lower bit error rate and higher data transfer rate. We found the efficiency of training mainly was from the edges of the phase patterns due to their stronger intensity changes between adjacent phase distribution. According to this characteristic, we proposed a method to only record and use the high frequency component of the phase patterns and to do the deep learning training. This method can improve the storage density due to reducing the material consumption.
The phase retrieval method based on deep learning can be used to solve the iterative problem in holographic data storage. The key of the deep learning method is to build the relationship between the phase data pages and the corresponding near-field diffraction intensity patterns. However, to build the correct relationship, thousands of samples of the training dataset are usually required. In this paper, according to the coding characteristics of phase data pages, we proposed an image segmentation method to greatly reduce the number of original training dataset. The innovation proposed by this new method lies in the special segmentation of the original samples to expand the number of samples.
Research of holographic storage security is of great significance to the development of holographic storage technology. To ensure the difficulty of cracking, the data reconstructed by the wrong key should present a statistically independent random noise distribution as far as possible. This paper studies collinear holographic encryption storage based on the orthogonal Hadamard matrix and random phase. After storing data with a particular key A in a regular ring shape, the secret key A can reconstruct the data. However, some other keys can also reconstruct partial data (crosstalk noise), and this crosstalk greatly reduced the security of the data storage system. Here, random orthogonal phase coding is proposed to solve the crosstalk problem, and the reference light was equally divided into 64 pieces. Each one consists of the same number of pixels at random positions in the circular reference light. The randomness of each reference pixel ensures the consistency of the reconstructed data light intensity, and the data can be completely eliminated due to the orthogonality of the reference light. The orthogonal reconstructed data presents a nearly statistical independent noise distribution, which has effectively reduced the similarity between the original data and the reconstructed data by a wrong key, avoided data leakage, and improved the security of holographic encryption storage.
A method for collinear non-interferometric phase retrieval holographic data storage using a single reference pixel is
proposed. The known embedded data of the signal beam in the traditional off-axis holographic data storage system is
placed in the reference beam through the collinear holographic data storage system, which greatly improves the material
utilization rate. And increasing the intensity of the reference beam can achieve phase retrieval using only one reference
pixel. As the intensity of the reference beam becomes stronger within a certain range, the number of iterations gradually
decreases. With this method, the phase retrieval can be achieved even when the total energy of the reference beam is less
than the signal beam. In the simulation, the four-level phase pattern was recorded and the phase was restored correctly.
Collinear holography data storage (CHDS) is a promising solution for “cold data” storage in the big data age. Studies adopt “amplitude type” and “phase type” orthogonal reference have been sequentially reported for the performance improvement of CHDS. Data from different users can be storage and readout separately by different orthogonal reference, which is meaningful for the application of security data storage. In this paper, a newly “phase type” orthogonal reference specified by a Hadamard orthogonal matrix is proposed for identity information storage. Each one Hadamard vector on behalf of a “phase type” reference, and the symbols “1” and “-1” in Hadamard matrix stands for the phase of 0 and pi of the reference pixel. Several different data pages are recorded using different orthogonal reference in advance, and there is only the specific data page which is matched to the orthogonal reference can be reproduced in the process of reconstruction. The action mechanism of orthogonal reference is analyzed, and the feasibility of the system is verified by numerical simulations and primary experiments.
The holographic performance of photo-polymeric material PQ/PMMA is found to be largely determined by pre-polymerization modulation, such as stirring time and pre-polymerization temperature, during the material preparation process. In the current study, in order to determine the best stirring time during the pre-polymerization process, the influence of stirring time on the holographic properties of PQ/PMMA here is seriously analyzed. Experimental observations clearly indicate that, under the same baking conditions, the diffraction efficiency of PQ/PMMA increase initially with the stirring time but then decrease as the stirring time continue increases. When the stirring time is 75 min, the holographic performance of PQ/PMMA reaches its best in which the diffraction efficiency of the material can reach up to 49.3%. Current study here determines the optimal stirring time and pre-polymerization temperature during the pre-polymerization process, thus provide an effective guidance for further preparation of PQ/PMMA photo-polymer materials with excellent holographic properties.
A single-shot non-interferometric phase retrieval method in holographic data storage is proposed to solve the problems that undetectability for phase by detector directly and unstability caused by interferometric detection. Embedded data are inserted in iterative Fourier transform algorithm to shorten iterations sharply. For avoiding embedded data occupying the code rate, we propose a collinear system to refer to the reference beam, which is always known, as the embedded data. Finally, fast stable phase information reading is realized because of single-shot non-interferometric detection and fast phase retrieval within only several iterations.
A non-interferometric phase retrieval method in collinear holographic data storage (HDS) is proposed. Noninterferometric system is stable which is suitable for phase-modulated HDS but non-interferometric phase retrieval algorithm replies on strong constraint to shorten iteration number. Embedded data can provide strong constraint. However, in off-axis system, embedded data have to be in the signal part which sacrifice code rate. Our proposed collinear system considers the reference beam as embedded data to increase the code rate by about 2 times.
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.
In this paper, we propose a frequency expanded method based on non-interferometric phase retrieval which can retrieve complex multi-level phase image by using only 1 times Nyquist frequency. Our proposed method utilizes the property of frequency spectrum periodicity and is the unique method with non-interferometry due to the intensity detection directly on the Fourier domain. For a regular phase image, same spacial frequency means same spectrum width. We choose a rectangular window with the same spacial frequency to the phase image and consider normalized Fourier intensity distribution of the rectangular window as the envelope of that of the phase image. After normalizing the spectrum of the phase image, we can expand its Fourier frequency with 1 times Nyquist size to other higher order frequency positions. Therefore, we can generate high-order frequencies artificially from low-order frequency which help us to retrieve phase image accurately and quickly.
Non-interferometric phase retrieval is a fundamental technique for phase-modulated holographic data storage due to its advantages of easy implementation, simple system setup, and robust noise tolerance. Usually, the iterative algorithm of non-interferometry needs hundreds of iteration numbers to retrieve phase accurately, which decreased the data transfer rate severely. Strong constraint conditions, such as embedded data, can be used on the phase data page to reduce the iteration numbers. However, introducing embedded data will reduce the code rate of the system. We proposed a method that combined the single-shot interferometric method with the non-interferometric iterative Fourier transform algorithm method. We used the phase decoding result by single-shot interferometry as the embedded data in the process of non-interferometry. Therefore, no extra embedded data are needed in the signal code. We realized the code rate improvement as well as keeping fast data transfer rate. In the demonstration, we recorded a four-level phase pattern and retrieved the phase correctly. The bit error rate of phase retrieval is less than 1% within 20 iterations, which proves our approach is practical. In our case, the code rate is increased by two times.
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