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Magnomechanically induced transparency and tunable slow-fast light via a levitated

OPTICS EXPRESS 2024年第9期32卷 14914-14928页

作者： Bayati, Sahar Harouni, Malek bagheri Mahdifar, Ali Univ Isfahan Dept Phys Esfahan *** Iran Univ Isfahan Dept Phys Quantum Opt Grp Esfahan *** Iran

In this paper, we theoretically investigate the magnomechanically induced transparency (MIT) phenomenon and slow -fast light propagation in a microwave cavity-magnomechanical system which includes a levitated ferromagnetic sphere. Magnetic dipole interaction determines the interaction between the photon, magnon, and center of mass motion of the cavity-magnomechanical system. As a result, we find that apart from coupling strength, which has an important role in MIT, the levitated ferromagnetic sphere's position provides us a parameter to manipulate the width of the transparency window. In addition, the control field's frequency has crucial influences on the MIT. Also this hybrid magnonic system allows us to demonstrate MIT in both the strong coupling and intermediate coupling regimes. More interestingly, we demonstrate tunable slow and fast light in this hybrid magnonic system. In other words, we show that the group delay can be adjusted by varying the control field's frequency, the sphere position, and the magnon-photon coupling strength. These parameters have an influence on the transformation from slow to fast light propagation and vice versa. Based on the recent experimental advancements, our results provide the possibility to engineer hybrid magnonic systems with levitated particles for the light propagation, and the quantum measurements and sensing of physical quantities.

关键词： Kerr effect Light matter interactions Light propagation Nonlinear optics applications optical data processing Slow light

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Design of a compact off-axis two-mirror freeform optical antenna for shaping and transmitting an elliptical beam emitted by laser diode

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APPLIED OPTICS 2024年第1期63卷 239-248页

作者： Chen, Xin Hu, Lizhong Liu, Jianing Wang, Chaoxiang Bai, Chenxi Zheng, Yifan Qin, Yan Yang, Huajun Jiang, Ping Univ Elect Sci & Technol China Sch Phys Chengdu 611731 Sichuan Peoples R China Beihang Univ Sch Instrumentat & Optoelect Engn Beijing 100191 Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Sichuan Peoples R China

Elliptical Gaussian beams generated by laser diodes (LDs) often exhibit asymmetrical divergence angle distribution, which limits their practical applications. In this study, we propose what we believe is a novel approach to shape and collimate the elliptical output beam from a LD. The design process involves the construction of two freeform reflective surfaces on a reference circle using a three-dimensional point-by-point iterative method, based on the law of conservation of energy, the vector reflection theory, and Fermat's principle. The output beam's maximum divergence angle is effectively compressed to 3.1579 mrad. The design is compact with a folded optical path and antenna size of 368.8 cm3. This paper presents a comprehensive design and optimization process, along with an in-depth analysis of the system's performance, thereby offering novel insights for emerging optical design practitioners. (c) Optica Publishing Group

关键词： Diffractive optical elements Diode lasers optical antennas optical components optical data processing optical systems

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Fundamentals and recent developments of free-space optical neural networks

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JOURNAL OF APPLIED PHYSICS 2024年第3期136卷 030701-030701页

作者： McNeil, Alexander Montes Li, Yuxiao Zhang, Allen Moebius, Michael Liu, Yongmin Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA Charles Stark Draper Lab Cambridge MA 02139 USA Charles Stark Draper Lab Cambridge MA 02139 USA Northeastern Univ Dept Mech & Ind Engn Boston MA 02115 USA

Machine learning with artificial neural networks has recently transformed many scientific fields by introducing new data analysis and information processing techniques. Despite these advancements, efficient implementation of machine learning on conventional computers remains challenging due to speed and power constraints. optical computing schemes have quickly emerged as the leading candidate for replacing their electronic counterparts as the backbone for artificial neural networks. Some early integrated photonic neural network (IPNN) techniques have already been fast-tracked to industrial technologies. This review article focuses on the next generation of optical neural networks (ONNs), which can perform machine learning algorithms directly in free space. We have aptly named this class of neural network model the free space optical neural network (FSONN). We systematically compare FSONNs, IPNNs, and the traditional machine learning models with regard to their fundamental principles, forward propagation model, and training process. We survey several broad classes of FSONNs and categorize them based on the technology used in their hidden layers. These technologies include 3D printed layers, dielectric and plasmonic metasurface layers, and spatial light modulators. Finally, we summarize the current state of FSONN research and provide a roadmap for its future development. (c) 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license

关键词： optical data processing

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Plasmonic modulators based on enhanced interaction between graphene and localized transverse-electric plasmonic mode

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OPTICS EXPRESS 2024年第23期32卷 40730-40740页

作者： Hou, Anle Wang, Yulin Geng, Feihu Zhang, Yong Huang, Chengping Zhou, Lin Nanjing Tech Univ Dept Phys Nanjing 210009 Peoples R China Nanjing Univ Key Lab Intelligent Opt Sensing & Manipulat Jiangsu Key Lab Artificial Funct Mat Minist EducColl Engn & Appl SciNatl Lab Solid St Nanjing 210093 Peoples R China

Active plasmonic modulators with high modulation depth, low energy consumption, ultra-fast speed, and small footprint are of interest and particular significance for nanophotonics and integrated optics. Here by constructing a transverse-electric (TE) plasmonic mode and maximizing the in-plane component localized on the graphene surface, we propose a high performing plasmonic modulator based on a graphene/split ring-like plasmonic waveguide (SRPW) system with a record high modulation depth (20.46 dB/mu m) and suppressed insertion loss (0.248 dB/mu m) at telecom wavelength 1310 nm, simultaneously possessing pronounced advantage in broadband ability (800-1650 nm) and superior electrical performance with energy consumption of 0.43 fJ/bit and modulation speed of 200 GHz. This innovative design provides a novel approach and idea for enhancing the interaction between light and matter in the waveguide system and will certainly inspire new schemes for the development of on-chip integrated optoelectronic devices.

关键词： Dielectric waveguides Effective refractive index optical data processing optical resonators Plasmon waveguides Silicon modulators

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Pattern recognition system based on a coherent diffractive correlator with deep learned processing of downsampled correlation responses

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APPLIED OPTICS 2024年第36期63卷 9196-9204页

作者： Goncharov, Dmitriy s. Starikov, Rostislav s. Zlokazov, E. V. G. E. N. I. I. Yu. Natl Res Nucl Univ Moscow Engn Phys Inst MEPhI Moscow 115409 Russia

Deep convolutional neural networks are known for high precision of object recognition;however, processing of high-resolution images with the use of high-resolution kernels requires a lot of calculations during training and inference. optical Fourier-processors and correlators provide highly parallel calculations that are robust to electromagnetic interference and potentially energy efficient. Article results demonstrate that the correlation pattern recognition problem can be efficiently solved by implementation of deep neural network for processing of downsampled output signals of coherent diffractive correlators. The results of neural network-based correlation processor architecture study, numerical training, and experimental implementation are presented and discussed in the article. It is shown that output signals of optical correlators being captured by a low-resolution sensor can be efficiently classified by a deep neural network that was trained on a numerically generated laboratory database of correlation responses. The use of auto-correlation peak-narrowing techniques such as phase modulation and contouring of input images or application of optimized distortion-invariant filters allow us to unify the form of auto-correlation peaks such that there is no need for retraining of the network if the target object is changed. Application of three trained network models with input layer sizes of 32 x 32, 16 x 16, and 8 x 8 for processing the downsampled correlation responses of different experimental implementations of 4-f and 1-f coherent diffractive correlators optoelectronic schemes, which include the schemes based on binary spatial light modulation, proved the possibility to perform recognition of objects on 256 x 256 images with precision above 92% and potential processing speed of more than 1000 frames per second. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologi

关键词： Modulation techniques Neural networks optical correlators optical data processing Pattern recognition Phase modulation

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Topological state transitions of skyrmionic beams under focusing configurations

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OPTICS EXPRESS 2024年第3期32卷 4167-4179页

作者： Cao, Shulei Du, Luping Shi, Peng Yuan, Xiaocong Shenzhen Univ Inst Microscale Optoelect Nanophoton Res Ctr Shenzhen 518060 Peoples R China Shenzhen Univ State Key Lab Radio Frequency Heterogeneous Integ Shenzhen 518060 Peoples R China Res Inst Intelligent Sensing Res Ctr Humanoid Sensing Zhejiang Lab Hangzhou 311100 Peoples R China

The recent emerging appearance of optical analogs of magnetic quasiparticles, i.e., optical skyrmions constructed via spin, field, and Stokes vectors, has garnered substantial interest from deep-subwavelength imaging and quantum entanglement. Here, we investigate systematically the topological state transitions of skyrmionic beams constructed by the Stokes vectors in the focusing configuration. We theoretically demonstrated that in the weak focusing, the skyrmion topological number is protected. Whereas, in the tight focusing, a unique topological transformation with skyrmion number variation is exhibited for the optical skyrmion, antiskyrmion, and 2nd-order skyrmion structures. The significant difference between the topological state transitions of these two cases originates from the transformation from the paraxial optical system to the nonparaxial optical system, and the approximate two-dimensional polarization structure to the three-dimensional polarization structure. The results provide new insights into the topological state transitions in topological structures, which promote applications in information processing, data storage, and free-space optical communications.

关键词： Free space optics Information processing Nonlinear photonic crystals optical data processing Quantum imaging Surface plasmon polaritons

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optical hyperdimensional soft sensing: speckle-based touch interface and tactile sensor

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OPTICS EXPRESS 2024年第3期32卷 3209-3220页

作者： Kitagawa, Kei Tsuji, Kohei Sagehashi, Koyo Niiyama, Tomoaki Sunada, Satoshi Kanazawa Univ Grad Sch Nat Sci & Technol Kakuma Machi Kanazawa Ishikawa 9201192 Japan Kanazawa Univ Inst Sci & Engn Fac Mech Engn Kakuma Machi Kanazawa Ishikawa 9201192 Japan

Hyperdimensional computing (HDC) is an emerging computing paradigm that exploits the distributed representation of input data in a hyperdimensional space, the dimensions of which are typically between 1,000-10,000. The hyperdimensional distributed representation enables energy-efficient, low-latency, and noise-robust computations with low-precision and basic arithmetic operations. In this study, we propose optical hyperdimensional distributed representations based on laser speckles for adaptive, efficient, and low-latency optical sensor processing. In the proposed approach, sensory information is optically mapped into a hyperdimensional space with >250,000 dimensions, enabling HDC-based cognitive processing. We use this approach for the processing of a soft-touch interface and a tactile sensor and demonstrate to achieve high accuracy of touch or tactile recognition while significantly reducing training data amount and computational burdens, compared with previous machine-learning-based sensing approaches. Furthermore, we show that this approach enables adaptive recalibration to keep high accuracy even under different conditions. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Deep learning Information processing Laser speckle optical computing optical data processing Speckle patterns

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Multi-channel broadband nonvolatile programmable modal switch

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OPTICS EXPRESS 2024年第7期32卷 10979-10999页

作者： Alquliah, Amged Ha, Jeongho Ndao, Abdoulaye Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

Mode-division multiplexing (MDM) in chip-scale photonics is paramount to sustain data capacity growth and reduce power consumption. However, its scalability hinges on developing efficient and dynamic modal switches. Existing active modal switches suffer from substantial static power consumption, large footprints, and narrow bandwidth. Here, we present, for the first time, to the best of our knowledge, a novel multiport, broadband, non-volatile, and programmable modal switch designed for on-chip MDM systems. Our design leverages the unique properties of integrating nanoscale phase-change materials (PCM) within a silicon photonic architecture. This enables independent manipulation of spatial modes, allowing for dynamic, non-volatile, and selective routing to six distinct output ports. Crucially, our switch outperforms current dynamic modal switches by offering non-volatile, energy-efficient multiport functionality and excels in performance metrics. Our switch exhibits exceptional broadband operating bandwidth exceeding 70 nm, with low loss (< 1 dB), and a high extinction ratio (> 10 dB). Our framework provides a step forward in chip-scale MDM, paving the way for future green and scalable data centers and high-performance computers. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Erbium-doped fiber amplifiers Extinction ratios Modulation techniques optical data processing Phase shift Wavelength division multiplexing

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In vivo and in situ robust quantitative optical biopsy of hepatocellular carcinoma and metastasis based on two-photon autofluorescence imaging

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OPTICS LETTERS 2024年第14期49卷 4054-4057页

作者： Song, Naikun Gu, Bobo Shanghai Jiao Tong Univ Sch Biomed Engn Shanghai 200030 Peoples R China

Two-photon autofluorescence (TPAF) imaging is able to offer precise cellular metabolic information with high spatiotemporal resolution, making it a promising biopsy tool. The technique is greatly hampered by the complexity of either the optical system or data processing. Here, the excitation wavelength was optimized to simultaneously excite both flavin adenine dinucleotide and nicotinamide adenine dinucleotide and eliminate the unexpected TPAF. The optical redox ratio (ORR) images were robustly achieved without additional calibration under the optimized single-wavelength excitation. The in vitro, , ex vivo, , and in vivo biopsy by the TPAF method were systematically studied and compared using hepato-cellular carcinoma and metastasis as examples. It was demonstrated that the proposed TPAF method simplified the optical system, improved the robustness of ORR, and enabled early-stage cancer diagnosis, showing distinguished advantages as compared with previous methods. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Bandpass filters Imaging techniques optical data processing optical imaging optical systems Spatial resolution

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Integrated multimode optical waveguides in glass using laser induced deep etching

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APPLIED OPTICS 2024年第4期63卷 895-903页

作者： Reitz, Birger Evertz, Andreas Basten, Robin Wurz, Marc Christopher Overmeyer, Ludger Leibniz Univ Hannover Inst Transport & Automat Technol Hannover Germany Cluster Excellence PhoenixD Photon Opt & Engn Inno Cluster Excellence PhoenixD Hannover Germany Leibniz Univ Hannover Inst Micro Prod Technol Hannover Germany

Glass is an ideal material for optical applications, even though only a few micromachining technologies for material ablation are available. These microstructuring methods are limited regarding precision and freedom of design. A micromachining process for glass is laser induced deep etching (LIDE). Without generating micro-cracks, introducing stress, or other damages, it can precisely machine many types of glass. This work uses LIDE to subtractive manufacture structures in glass carrier substrates. Due to its transmission characteristics and refractive index, the glass substrate serves as optical cladding for polymer waveguides. In this paper, the described fabrication process can be divided into two sub-steps. The doctor blade technique and subsequent additive process step is used in manufacturing cavities with U-shaped cross-sections in glass in order to fill the trenches with liquid optical polymers, which are globally UV-cured. Based on the higher refractive index of the polymer, it enables optical waveguiding in the visible to near-infrared wavelength range. This novel, to the best of our knoowledge, manufacturing method is called LDB (LIDE -doctor -blade);it can be the missing link between long-distance transmissions and on -chip solutions on the packaging level. For validation, optical waveguides are examined regarding their geometrical dimensions, surface roughness, and waveguiding ability, such as intensity distribution and length-dependent attenuation.

关键词： Glass waveguides Laser glass optical data processing optical materials Polymer waveguides Refractive index

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