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A novel position-shift method of double-phase fresnel hologram for synthesizing a complex fresnel hologram 2nd

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A novel position-shift method of double-phase fresnel hologr...

2nd International Conference on Sensor Networks and signal processing, SNSP 2019

作者： Shen, Chuan Zhu, QinQin Hong, QingQing Zhang, Cheng Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Key Laboratory of Modern Imaging and Display Technology of Anhui Province Anhui University Hefei230601 China

ISBN: (纸本)9789811549168

An ideal desired spatial light modulator that is capable of complex amplitude modulation will be one of the ultimate tools for holographic display. In this paper, an analytical method to overlap double-phase Fresnel holograms displayed on the phase-only spatial light modulators for synthesizing a complex Fresnel hologram is proposed. Two $$4f$$ configurations with the phase-only spatial light modulator inserted in the Fourier plane are employed. Different programmable blazed phase gratings can be easily implemented by encoding their phase functions onto the spatial light modulators. We theoretically analyze the implementation of the proposed system based on Fourier optics. The effects introduced by the discrete pixelated nature of the spatial light modulator are assessed. A $$4f$$ configuration of holographic display system based on two liquid crystals on silicons is designed to indicate the free position-shift of the hologram. Optical reconstructions yield satisfactory results. © Springer Nature Singapore Pte Ltd 2021.

关键词： Holographic displays

A Hybrid Iterative Neural Solver Based on Spectral Analysis for Parametric PDEs

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arXiv 2024年

作者： Cui, Chen Jiang, Kai Liu, Yun Shu, Shi Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Recently, deep learning-based hybrid iterative methods (DL-HIM) have emerged as a promising approach for designing fast neural solvers to tackle large-scale sparse linear systems. DL-HIM combine the smoothing effect of simple iterative methods with the spectral bias of neural networks, which allows them to effectively eliminate both high-frequency and low-frequency error components. However, their efficiency may decrease if simple iterative methods can not provide effective smoothing, making it difficult for the neural network to learn mid-frequency and high-frequency components. This paper first conducts a convergence analysis for general DL-HIM from a spectral viewpoint, concluding that under reasonable assumptions, DL-HIM exhibit a convergence rate independent of grid size h and physical parameters µ. To meet these assumptions, we design a neural network from an eigen perspective, focusing on learning the eigenvalues and eigenvectors corresponding to error components that simple iterative methods struggle to eliminate. Specifically, the eigenvalues are learned by a meta subnet, while the eigenvectors are approximated using Fourier modes with a transition matrix provided by another meta subnet. The resulting DL-HIM, termed the Fourier Neural Solver (FNS), can be trained to achieve a convergence rate independent of grid size and PDE parameters by designing a loss function that ensures the neural network complements the smoothing effect of Jacobi iterative methods. We verify the performance of FNS on six types of linear parametric *** Codes 65F10, 65F08, 68T07, 65N22, 90C06 Copyright © 2024, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

NetPrompt: Neural Network Prompting Enhances Event Extraction in Large Language Models

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IEEE Transactions on Big Data 2025年

作者： Mu, Lin Cheng, Yide Shen, Jun Zhang, Yiwen Zhong, Hong School of Computer Science and Technology Anhui University Anhui Hefei230601 China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education the Anhui Engineering Laboratory of IoT Security Technologies the School of Computer Science and Technology the Institute of Physical Science and Information Technology Anhui University Hefei230039 China

Event Extraction involves extracting event-related information such as event types and event arguments from context, which has long been tackled through well-designed neural networks or fine-tuned pre-trained language models. These approaches require substantial annotated data for tuning parameters and are resource-intensive. Recently, Prompting strategies with frozen parameters, such as Chain-of-Thought and Self-Consistency, have delivered success in NLP using LLMs by generating intermediate thought steps. However, they suffer from the challenge of error propagation and lack of interaction between different thoughts. In this paper, we propose Neural Network-based Prompting (NetPrompt), a novel network-structured prompting strategy for event extraction. The core idea behind NetPrompt is to imitate the excellent information integration capabilities of neural network structures. Specifically, we first decompose the event extraction problem into diverse intermediate subtasks, and each subtask is represented as a node in different layers of the network, the output of the nodes in the preceding layer is fed into the subsequent layer. Secondly, we propose pruning strategies to adapt the reasoning overhead to different problems. Finally, we have conducted extensive experiments on two widely used event extraction benchmarks to evaluate NetPrompt. The results demonstrated that NetPrompt significantly improved the event extraction performance compared to previous methods. ©2015 IEEE.

关键词： Neural network models

Momentum-Accelerated Richardson(m) and Their Multilevel Neural Solvers

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arXiv 2024年

作者： Wang, Zhen Liu, Yun Cui, Chen Shu, Shi Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Recently, designing neural solvers for large-scale linear systems of equations has emerged as a promising approach in scientific and engineering computing. This paper first introduce the Richardson(m) neural solver by employing a meta network to predict the weights of the long-step Richardson iterative method. Next, by incorporating momentum and preconditioning techniques, we further enhance convergence. Numerical experiments on anisotropic second-order elliptic equations demonstrate that these new solvers achieve faster convergence and lower computational complexity compared to both the Chebyshev iterative method with optimal weights and the Chebyshev semi-iteration method. To address the strong dependence of the aforementioned single-level neural solvers on PDE parameters and grid size, we integrate them with two multilevel neural solvers developed in recent years. Using alternating optimization techniques, we construct Richardson(m)FNS for anisotropic equations and NAG-Richardson(m)-WANS for the Helmholtz equation. Numerical experiments show that these two multilevel neural solvers effectively overcome the drawback of single-level methods, providing better robustness and computational efficiency. Copyright © 2024, The Authors. All rights reserved.

关键词： Iterative methods

Convergent analysis of algebraic multigrid method with data-driven parameter learning for non-selfadjoint elliptic problems

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arXiv 2024年

作者： Zhang, Juan Luo, Junyue Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

In this paper, we apply the practical GADI-HS iteration as a smoother in algebraic multigrid (AMG) method for solving second-order non-selfadjoint elliptic problem. Additionally, we prove the convergence of the derived algorithm and introduce a data-driven parameter learing method called Gaussian process regression (GPR) to predict optimal parameters. Numerical experimental results show that using GPR to predict parameters can save a significant amount of time cost and approach the optimal parameters accurately. © 2024, CC BY.

关键词： Algebra

Optically transparent transmissive orbital angular momentum (OAM) metasurface with high transmittance and broadband characteristics

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Optics Express 2025年第12期33卷 24385-24395页

作者： Yong Cai Yuying Dai Yue Ma Gang Wang Guanghui Xu Xingang Ren Hui Wang Xiaohu Zhao Xianliang Wu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei 230039 China Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes Anhui University Hefei 230039 China wang_toward@*** ghxu86@*** Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei 230039 China xgren@*** Hefei Normal University Hefei 230009 China

This work proposes a high-performance broadband orbital angular momentum (OAM) beam-generating metasurface based on optically transparent media. A broadband polarization-converting transmissive metasurface, which operates in the 18 - 24 (28.57% fractional bandwidth) GHz range, has been realized by collaboratively designing dual C-split ring resonator structures and bidirectional lattice-patterned surface networks. The array structure demonstrates typical helical phase distribution features in the K-band, and experimental results verify simulation design. Innovatively employing a composite structure of quartz glass substrate and patterned conductive thin films, the design achieves compatible optimization of 77% visible-light transmittance and microwave broadband performance. This approach breaks through the mutually exclusive limitations of traditional metasurfaces’ optical/electromagnetic properties, providing a highly integrated solution for transparent antenna radomes in satellite communication systems and multi-mode beam multiplexing applications.

关键词： Orbital angular momentum multiplexing Phase plates Ring resonators Spatial light modulators Spiral phase Thin films

Broadband infrared absorber based on metamaterial

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Broadband infrared absorber based on metamaterial

2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Kang, Meijun Feng, Jian Rong, Mandi Fang, Ming The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Anhui Hefei230039 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Anhui Luan237000 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China State Key Laboratory of Millimeter Waves Southeast University Nanjing214135 China

ISBN: (纸本)9781665452366

In order to obtain an absorber with high absorption efficiency and wide absorption band, a metamaterial structure by Metal-ENZ-Insulator-Metal (MEIM) is designed, and its absorption in the 130-230 THz band is calculated using the simulation software frequency-domain solver. By rotating the upper metal layer and the lower hollow layer, the simulation results can be slightly disturbed. In addition, the introduction of the epsilon-near-zero (ENZ) media will also affect the bandwidth and absorption of the absorber. Therefore, the high absorption and wide bandwidth of the absorber are achieved by the size of the structure, the rotation angle of the corresponding structure,and the clever application of the ITO layer. © 2022 IEEE.

关键词： Metamaterials

A virtual element method with IMEX-SAV scheme for the incompressible magnetohydrodynamics equations

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arXiv 2024年

作者： Dong, Xiaojing Huang, Yunqing Wang, Tianwen Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

This paper proposes a virtual element method (VEM) combined with a second-order implicit-explicit scheme based on the scalar auxiliary variable (SAV) method for the incompressible magnetohydrodynamics (MHD) equations. We employ the BDF2 scheme for time discretization and a conservative VEM for spatial discretization, in which the mass conservation in the velocity field is kept by taking advantage of the virtual element method’s adaptability and its divergence-free characteristics. In our scheme, the nonlinear terms are handled explicitly using the SAV method, and the magnetic field is decoupled from the velocity and pressure. This decoupling only requires solving a sequence of linear systems with constant coefficient at each time step. The stability estimate of the fully discrete scheme is developed, demonstrating the scheme is unconditionally stable. Moreover, rigorous error estimates for the velocity and magnetic field are provided. Finally, numerical experiments are presented to verify the valid of theoretical analysis. © 2024, CC BY-NC-ND.

关键词： Discrete element methods

Conservative nonconforming virtual element method for stationary incompressible magnetohydrodynamics

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arXiv 2024年

In this paper, we propose a conservative nonconforming virtual element method for the full stationary incompressible magnetohydrodynamics model. We leverage the virtual element satisfactory divergence-free property to ensure mass conservation for the velocity field. The condition of the well-posedness of the proposed method, as well as the stability are derived. We establish optimal error estimates in the discrete energy norm for both the velocity and magnetic field. Furthermore, by employing a new technique, we obtain the optimal error estimates in L2-norm without any additional conditions. Finally, numerical experiments are presented to validate the theoretical analysis. In the implementation process, we adopt the effective Oseen iteration to handle the nonlinear system. © 2024, CC BY-NC-ND.

关键词： Magnetohydrodynamics