Due to the rapid development of information technology, the demand for data storage is gradually increasing. People urgently need a storage technology with large capacity, high speed, and low energy consumption to alleviate the storage pressure brought by current data growth. Collinear holographic data storage system has the advantages of high storage density, system stability, simple structure, and miniaturization, which becomes a research hotspot for the new generation of storage technology. Among them, holographic storage materials are the key to improve the performance of holographic storage technology, and the lifespan of storage materials determines the security, integrity, and accessibility of data. However, traditional recording pattern is sensitive to the recording position due to strict bragg condition. It is difficult to accurately locate the recording position when the material is put back in the system after aging experiment. We design a positioning map to help quick locating. The displacement selectivity of the positioning map is poor, which is easy to find in a large range, and the positioning map pattern can be exposed for a long time without disappearing. The polymethyl methacrylate (PQ/PMMA) photopolymer materials doped with phenanthraquinone was tested on the collinear holographic data storage system. The low bit error rate of the material reading data page proved that the design scheme was feasible, and provided a basis for the follow-up study of material life.
KEYWORDS: Data storage, Image segmentation, Holography, Deep learning, Holographic data storage systems, Neural networks, Education and training, Data modeling, Mathematical optimization, Holograms
Experiments have shown that deep learning can improve the data reading of holographic data storage. However, it requires a large amount of storage materials and time to obtain data to optimize the network model. In data encoding, each encoded data page consists of 51sub-pages with the same structure. This paper proposes a deep learning method for image segmentation based on encoding features in collinear holographic data storage. Using a deep learning method of image segmentation, the encoded data page is segmented into data sub-pages. It can reduce material loss and data collection time.
Although polarization holography introduces polarization dimensions, it is well known that polarization has only two orthogonal dimensions, and the expansion of recording capabilities is limited. Therefore, we introduce the polarization encoding for theoretical analysis and calculation, the orthogonal polarization array of arbitrary dimensions is obtained. Assuming that the n-dimensional vectors Q1, Q2, …, and Qx are a group of non-zero vectors that are orthogonal to each other in the orthogonal polarization array. The Schmidt orthogonalization method is used to expand the column vector group of the n-dimensional orthogonal polarization array into a set of canonical orthogonal basis of the space Kn. During the experiment, when the signal S1 is recorded with Q1, it can be faithfully reconstructed with Q1, while it shows null reconstruction with Q2 or Qx. By analogy, multiple recording and independent reconstruction experiments are carried out successively.
In the field of holographic storage, poly (methyl methacrylate) (PQ/PMMA) photopolymer doped with phenanthraquinone has the characteristics of controllable material thickness, polarization sensitivity, and simple manufacturing process, demonstrating good research value and application prospects. This paper prepared PQ/PMMA materials with thicknesses of 0.3, 0.5, 1.0, 1.5, 2.0, 3.0, and 4.0 mm, and analyzed the holographic characteristics of PQ/PMMA materials with different thicknesses, such as diffraction efficiency, photosensitivity, refractive index modulation, etc. By comparing the holographic performance parameters of materials with different thicknesses, it was found that as the thickness increases, the saturation diffraction efficiency shows a trend of first increasing and then decreasing. The 3.0 mm thick PQ/PMMA material has higher saturation diffraction efficiency and photosensitivity, providing a basis for optimizing material preparation parameters.
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: Data modeling, Signal to noise ratio, Deep learning, Holographic data storage systems, Holography, Data storage, Education and training, Objectives, Neural networks, Reliability
In recent years, optical holographic data storage system has gradually become a research hotspot and a strong competitor of big data storage due to its high data transfer rate, long storage life and high storage density. In the collinear amplitude modulated holographic data storage system, in order to improve the storage density, a high magnification objective lens is usually used as the recording lens to record the encoded data pages in the holographic storage medium. Therefore, when the objective lens is focused on the holographic storage medium, the accuracy and reliability of data recording and reading can be guaranteed. However, in the process of normal use of the system, environmental interference and other factors will inevitably lead to defocusing of the objective lens, which will result in high bit-error-rate (BER) and low signal-to-noise ratio (SNR) of the recorded and read coding information, affecting the accuracy and reliability of information reading. In this paper, we propose a collinear amplitude modulated holographic data storage system objective defocusing correction model using deep learning. Only a training model with defocusing distance of 100μm can be used to correct the defocusing of the objective lens with defocusing distance less than 100μm. The reconstructed BER is reduced to less than 1/10 of the original data, and the SNR is increased to more than 5 times of the original data. The reliability and accuracy of system record reading are improved.
This paper analyzed the security of random phase encryption holographic storage technology. Taking binary random phase as an example, the recorded hologram is continually readout by series guessing reference. The experiment showed that the correlation coefficient between readout information and the recorded information was firstly decreased and then increased when the phase correct ratio of guessing reference is increased from 0% to 100%. The recorded information can’t be readout at all when the phase correct ratio of guessing reference range from 40% to 60%. Since the guessing reference with phase correct ratio between 40% and 60% has occupied majority guessing cases, the recorded information can’t be cracked in most cases. This indicates the high security of the random phase encryption storage technique.
Amplitude-modulated collinear holographic data storage technology has high storage density, fast data transfer rate and stable system. The key to realizing system operation is to decode the amplitude code quickly and correctly. We proposed a decoding method based on 3:16 amplitude code. We used the convolution calculation to locate the sync mark point of every sub-page in the data page quickly and calculated the magnification rates among sub-pages to get the correct sub-page image segmentation. Taking the bit error rate as the evaluation standard, we verified our method successfully in different image quality.
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.
In this letter, we employ vector wave polarization holography theory based on the dielectric tensor description. Newly developed vector wave polarized holography theory breaks up the limitation of paraxial approximation in polarization holograms. Various interesting phenomena have been investigated, the faithful reconstruction is of particular significance. The faithful reconstruction (FR) effect indicates that the polarization state of the reconstruction wave is identical to that of the signal wave, it can be achieved process when the intensity and polarization holographic grating attained a balance during after exposure. The FR property related to the linearly, circularly and elliptically polarization is investigated in our previous work. In our experiment, the recording medium we use is the bulk polarization holographic recording material of phenanthrenequinone-doped polymethyl methacrylate photopolymer (PQ-PMMA). The mixed mass ratio of methyl methacrylate (MMA), azobisisobutyronitrile (AIBN) and phenanthrenequinone (PQ) are 100:1:1. Under the cross-angle of π/2 inside the recording media, the polarized holographic reconstruction of the circular polarization recorded by a horizontal linear polarization wave is calculated. It is found that the circularly polarized signal can be faithful reconstruction by arbitrarily polarized reading waves. However, when the polarization of the reading wave is orthogonal to the polarization of the reference wave, it will occur the null reconstruction (NR). The FR technology will provide a simpler and more effective method for a circular polarization generator. At the same time, the NR technology can quickly detect that the polarized wave is vertical polarization.
Polarization holography has great potential in Ultra-high-definition (UHD) information diplay and data storage. Due to the faithful reconstruction in polarization holography, the storage capacity is further improved easily. In this paper, a device for generating vector vortex beam is demonstrated using the faithful reconstruction characteristics. Through the analysis of the experimental results, it is found that the helical phase order corresponding to different polarization states is different in the transmission process. It shows the independence of vector vortex beam propagation. This method has a certain research space in optical storage, and application prospect in optical micromanipulation optical tweezers.
Phase-modulated holographic data storage shows a great prospect in Ultra-high-definition (UHD) information display and data storage due to its higher capacity than amplitude modulation. However, the phase reconstruction is more sensitive to noise in the spectrum plane. In this paper, we proposed to use the low-depth camera to obtain the spectral intensity of the reconstructed beam, and used iterative Fourier transform algorithm to retrieve phase. Simulation and experiment show that this method has stronger noise suppression performance.
We used the amplitude coding method of 3:16, that is, in a 4 * 4 pixel matrix, only three pixels are in the on state, and the remaining pixels are in the off state. In the collinear amplitude holographic data storage system, U-Net full convolution neural network is used to denoise the amplitude coded image obtained by the detector. The experimental results show that the bit error rate can be reduced to less than 1% from 10% and the image signal-to-noise ratio can be increased by more than 5 times.
Biological tissue is a multiple random scattering medium. The study of the propagation of acousto-optic signals in biological tissues is an important and complex issue in acousto-optical tomography(AOT). In this paper, the finite element simulation software COMSOL Multiphysics is used to simulate the propagation of acousto-optic signal modulated by ultrasound in double-layer tissue. The effects of different types of ultrasounds on acousto-optic signals in tissues are studied. The influence of the optical properties of the target tissue and non-target tissue on the acousto-optic signal in the double-layered tissue is also discussed. The simulation results show that the waveform of the acousto-optic signal is very similar to that of the ultrasonic wave. The acousto-optic signal presents a periodic variation as the ultrasonic frequency changes. The peak-to-peak value and average value of the acousto-optic signal are affected by the optical properties of double-layer tissue. However, the modulation depth of the acousto-optic signal only depends on the optical characteristics of the tissue in the ultrasound focal zone (target tissue), and has nothing to do with the optical characteristics of the tissue outside the ultrasound zone (non-target tissue). The modulation depth has a good antiinterference performance, which is conducive to image processing and reconstruction in AOT.
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.
The concentration of photosen-sitizer is an important factor affecting the properties of holographic materials. Most researchers use doping or copolymerization methods to increase the saturation dissolvability of photo-sensitizer. However, the addition of multiple components will reduce the molecular mass of the photoproducts and the polymer substrate, resulting in poor stability of the grating. In this paper, we studied the solubility of phenanthraquinone (PQ) in MMA at different temperatures. At 60 °C, the solubility of PQ could reach 1.8%. Meanwhile, we found that the thermo-initiator concentration of 2,2-Azobis(AIBN) affected long-chain carbon polymerization. Therefore, proper concentration balance has a huge impact on the performance of the materials. Finally, we obtained a relatively suitable concentration balance of PQ/PMMA photopolymer, making it more suitable for volume holographic data storage.
This paper focuses on the causes of bubbles in the fabrication of holographic storage materials phenan- threnequinone(PQ)/polymethyl methacrylate(PMMA).Three main possibilities for generating bubbles are proposed.Azodiisobutyronitrile(AIBN) decomposes to generate nitrogen,which cannot diffuse to generate bubbles.The temperature is too high,and the local boiling of methyl methacrylate(MMA) produces bub- bles.Bubbles caused by changes in material volume.Simulation and experimental verification of the three cases show that the main reason for the generation of bubbles is the sudden shrinkage of the material.It is determined that the temperature is the second in uencing factor.
Stage IA endometrial cancer is the only candidate for conservative management. Therefore, early diagnosis of endometrial cancer is very important. Co-registered photoacoustic (PA) and ultrasonic (US) imaging system is available to detect early endometrial cancer (EEC) based on a cylindrical diffuser. To correctly detect and diagnose EEC from FIGO stage IA and stage IB by co-registered PA and US imaging system, a convolutional neural network (CNN) classifier of EEC for co-registered PA and US images was proposed. Activation function ReLU and the dropout technique were used in the CNN classifier. The experiment results show the area under the receiver operating characteristic curve of the proposed algorithm is 0.9998 with a sensitivity of 98.75% and specificity of 98.75%. The CNN classifier could be used in the computer-aided diagnosis for early endometrial cancer of the co-registered PA and US imaging system.
Biological tissue is a kind of complex and highly scattering medium. The study of the ultrasound-modulated scattered light propagation in biological tissue is a fundamental problem that must be solved in acousto-optic tomography (AOT). Due to the action of the ultrasonic field, the optical properties of the scattering medium change with time-space, and the propagation of light in it becomes more complicated. In this paper, the finite element simulation software COMSOL Multiphysics is used to simulate the propagation of light in biological tissue under the action of different types of ultrasonic field. The effects of ultrasonic field distribution, ultrasonic intensity and frequency on the light diffusion in the scattered medium are studied. The relationship between the ultrasound-modulated scattering light and the optical properties of biological tissue is discussed. The numerical simulation results are in agreement with the experimental results.
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