Keyao Li 1,2†Yiming Wang 3†Dapu Pi 1Baoli Li 1[ ... ]Min Gu 1
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China
2 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
3 National Laboratory of Solid State Microstructures, and College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, China
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.
holographic encryption optical secret sharing cascaded liquid crystal hologram multi-dimensional multiplexing 
Opto-Electronic Advances
2024, 7(1): 230121
作者单位
摘要
1 上海理工大学光子芯片研究院,上海 200093
2 上海理工大学光电信息与计算机工程学院,上海 200093
近年来,受生物神经系统结构和功能的启发,神经形态计算引起广泛兴趣。忆阻器可以通过其电荷或磁通量调节电导,与人脑突触作用机制相似,是神经形态计算最有前途的候选器件之一。提出一种基于飞秒激光加工氧化石墨烯基忆阻器的方法,通过调整器件两端扫描电压,实现了极性可控的电阻开关:低电压下,器件表现出单极性电阻开关特性,在150个循环扫描中呈现高度稳定性,且功耗仅有0.75 nW;高电压下,器件呈现双极性开关特性。伴随测试次数的增加,器件整体电导逐步增加,同时分别讨论了两种电压下器件的开关机制。
极性可控 激光加工 氧化石墨烯 忆阻器 
激光与光电子学进展
2024, 61(3): 0323002
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China
2 School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
3 Nokia Shanghai Bell Co., Ltd., Shanghai 201206, China
4 College of Medical Instruments, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
Edge detection for low-contrast phase objects cannot be performed directly by the spatial difference of intensity distribution. In this work, an all-optical diffractive neural network (DPENet) based on the differential interference contrast principle to detect the edges of phase objects in an all-optical manner is proposed. Edge information is encoded into an interference light field by dual Wollaston prisms without lenses and light-speed processed by the diffractive neural network to obtain the scale-adjustable edges. Simulation results show that DPENet achieves F-scores of 0.9308 (MNIST) and 0.9352 (NIST) and enables real-time edge detection of biological cells, achieving an F-score of 0.7462.
diffractive neural network edge detection phase objects 
Chinese Optics Letters
2024, 22(1): 011102
Sheng-ke Zhu 1,2†Ze-huan Zheng 3†Weijia Meng 4,5Shan-shan Chang 1,2[ ... ]Jin-hui Chen 1,2,6,***
Author Affiliations
Abstract
1 School of Electronic Science and Engineering, Xiamen University, 361005 Xiamen, China
2 Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), 361005, Xiamen, China
3 School of Computer Science and Information Engineering, Xiamen Institute of Technology, 361021 Xiamen, China
4 Institute of Photonic Chips, University of Shanghai for Science and Technology, 200093 Shanghai, China
5 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, 200093 Shanghai, China
6 Shenzhen Research Institute of Xiamen University, 518000, Shenzhen, China
The complete description of a continuous-wave light field includes its four fundamental properties: wavelength, polarization, phase and amplitude. However, the simultaneous measurement of a multi-dimensional light field of such four degrees of freedom is challenging in conventional optical systems requiring a cascade of dispersive and polarization elements. In this work, we demonstrate a disordered-photonics-assisted intelligent four-dimensional light field sensor. This is achieved by discovering that the speckle patterns, generated from light scattering in a disordered medium, are intrinsically sensitive to a high-dimension light field given their high structural degrees of freedom. Further, the multi-task-learning deep neural network is leveraged to process the single-shot light-field-encoded speckle images free from any prior knowledge of the complex disordered structures and realizes the high-accuracy recognition of full-Stokes vector, multiple orbital angular momentum (OAM), wavelength and power. The proof-of-concept study shows that the states space of four-dimensional light field spanning as high as 1680=4 (multiple-OAM) $$\times$$ 2 (OAM power spectra) $$\times$$ 15 (multiple-wavelength) $$\times$$ 14 (polarizations) can be well recognized with high accuracy in the chip-integrated sensor. Our work provides a novel paradigm for the design of optical sensors for high-dimension light fields, which can be widely applied in optical communication, holography, and imaging.
PhotoniX
2023, 4(1): 26
Runze Li 1,2†Yibo Dong 1,2†Fengsong Qian 3Yiyang Xie 3[ ... ]Min Gu 1,2,***
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China
2 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
3 Key Laboratory of Optoelectronic Technology, Ministry of Education, Beijing University of Technology Beijing, China
The rapid development of neuromorphic computing has stimulated extensive research interest in artificial synapses. Optoelectronic artificial synapses using laser beams as stimulus signals have the advantages of broadband, fast response, and low crosstalk. However, the optoelectronic synapses usually exhibit short memory duration due to the low lifetime of the photo-generated carriers. It greatly limits the mimicking of human perceptual learning, which is a common phenomenon in sensory interactions with the environment and practices of specific sensory tasks. Herein, a heterostructure optoelectronic synapse based on graphene nanowalls and CsPbBr3 quantum dots was fabricated. The graphene/CsPbBr3 heterojunction and the natural middle energy band in graphene nanowalls extend the carrier lifetime. Therefore, a long half-life period of photocurrent decay - 35.59 s has been achieved. Moreover, the long-term optoelectronic response can be controlled by the adjustment of numbers, powers, wavelengths, and frequencies of the laser pulses. Next, an artificial neural network consisting of a 28 × 28 synaptic array was established. It can be used to mimic a typical characteristic of human perceptual learning that the ability of sensory systems is enhanced through a learning experience. The learning behavior of image recognition can be tuned based on the photocurrent response control. The accuracy of image recognition keeps above 80% even under a low-frequency learning process. We also verify that less time is required to regain the lost sensory ability that has been previously learned. This approach paves the way toward high-performance intelligent devices with controllable learning of visual perception.
PhotoniX
2023, 4(1): 4
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China
2 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
3 School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Significant progress has been made in computational imaging (CI), in which deep convolutional neural networks (CNNs) have demonstrated that sparse speckle patterns can be reconstructed. However, due to the limited “local” kernel size of the convolutional operator, for the spatially dense patterns, such as the generic face images, the performance of CNNs is limited. Here, we propose a “non-local” model, termed the Speckle-Transformer (SpT) UNet, for speckle feature extraction of generic face images. It is worth noting that the lightweight SpT UNet reveals a high efficiency and strong comparative performance with Pearson Correlation Coefficient (PCC), and structural similarity measure (SSIM) exceeding 0.989, and 0.950, respectively.
speckle reconstruction non-local model generic face images lightweight network 
Opto-Electronic Advances
2023, 6(2): 220049
Jing Wang 1,2,*Zhen Zhang 1,2Hongyu Shen 1,2Qi Wu 1,2Min Gu 1,2,**
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China
2 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China
The MINimal emission FLUXes (MINFLUX) technique in optical microscopy, widely recognized as the next innovative fluorescence microscopy method, claims a spatial resolution of 1–3nm in both dead and living cells. To make use of the full resolution of the MINFLUX microscope, it is important to select appropriate fluorescence probes and labeling strategies, especially in living-cell imaging. This paper mainly focuses on recent applications and developments of fluorescence probes and the relevant labeling strategy for MINFLUX microscopy. Moreover, we discuss the deficiencies that need to be addressed in the future and a plan for the possible progression of MINFLUX to help investigators who have been involved in or are just starting in the field of super-resolution imaging microscopy with theoretical support.The MINimal emission FLUXes (MINFLUX) technique in optical microscopy, widely recognized as the next innovative fluorescence microscopy method, claims a spatial resolution of 1–3nm in both dead and living cells. To make use of the full resolution of the MINFLUX microscope, it is important to select appropriate fluorescence probes and labeling strategies, especially in living-cell imaging. This paper mainly focuses on recent applications and developments of fluorescence probes and the relevant labeling strategy for MINFLUX microscopy. Moreover, we discuss the deficiencies that need to be addressed in the future and a plan for the possible progression of MINFLUX to help investigators who have been involved in or are just starting in the field of super-resolution imaging microscopy with theoretical support.
Fluorescence probes MINFLUX nanoscopy photoblinking super-resolution imaging labeling strategy 
Journal of Innovative Optical Health Sciences
2023, 16(1): 2230011
Xi Chen 1,2,*Min Gu 1,2,*
Author Affiliations
Abstract
1 Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China.
2 Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
The fabrication of high-resolution laser-scribed graphene devices is crucial to achieving large surface areas and thus performance breakthroughs. However, since the investigation mainly focuses on the laser-induced reduction of graphene oxide, the single-beam scribing provides a tremendous challenge to realizing subdiffraction features of graphene patterns. Here, we present an innovative 2-beam laser scribing pathway for the fabrication of subdiffraction graphene patterns. First, an oxidation reaction of highly reduced graphene oxide can be controllably driven by irradiation of a 532-nm femtosecond laser beam. Based on the oxidation mechanism, a 2-beam laser scribing was performed on graphene oxide thin films, in which a doughnut-shaped 375-nm beam reduces graphene oxide and a spherical 532-nm ultrafast beam induces the oxidation of laser-reduced graphene oxide. The spherical beam turns the highly reduced graphene oxide (reduced by the doughnut-shaped beam) to an oxidized state, splitting the laser-scribed graphene oxide line into 2 subdiffraction featured segments and thus forming a laser-scribed graphene/oxidized laser-scribed graphene/laser-scribed graphene line. Through the adjustment of the oxidation beam power, the minimum linewidth of laser-scribed graphene was measured to be 90 nm. Next, we fabricated patterned supercapacitor electrodes containing parallel laser-scribed graphene lines with subdiffraction widths and spacings. An outstanding gravimetric capacitance of 308 F/g, which is substantially higher than those of reported graphene-based supercapacitors, has been delivered. The results offer a broadly accessible strategy for the fabrication of high-performance graphene-based devices including high-capacity energy storage, high-resolution holograms, high-sensitivity sensors, triboelectric nanogenerators with high power densities, and artificial intelligence devices with high neuron densities.
Ultrafast Science
2022, 2(1): 0001
Author Affiliations
Abstract
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.
Opto-Electronic Science
2022, 1(9): 220004
成科 1,2,*胡晓楠 1,2贺瑜 1,2孟维佳 1,2[ ... ]方心远 1,2
作者单位
摘要
1 上海理工大学光子芯片研究院, 上海 200093
2 上海理工大学光电信息与计算机工程学院人工智能纳米光子学中心, 上海 200093
完美涡旋光束 (POVB) 是径向强度分布和半径均与光束轨道角动量 (OAM) 状态无关的一类涡旋光, 已被应用于光学操控、光通信、激光材料处理等领域。其中, POVB 轨道角动量状态的探测是关键且有挑战的技术。本研究通过并行梯度下降算法, 构建了光学衍射神经网络 (DNN), 实验上实现了轨道角动量阶数在-50~+50 范围内的 POVB 的识别。在此过程中, 衍射转换效率可达 58%。本研究为 POVB 的 OAM 探测提供了新的思路, 在 POVB 的各类应用中均存在潜在应用价值。
傅里叶光学 轨道角动量探测 光学衍射神经网络 完美涡旋光束 Fourier optics orbital angular momentum detection optical diffraction neural network perfect optical vortex beam 
量子电子学报
2022, 39(2): 262

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