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Passive on-chip isolators based on the thin-film lithium niobate platform

Chinese Physics B 2025年第3期34卷 408-413页

作者： Jiacheng Liu Gongyu Xia Qilin Hong Pingyu Zhu Kai-Kai Zhang keyu Xia Ping Xu Shiqiao Qin Zhihong Zhu College of Advanced Interdisciplinary Studies&Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Institute for Quantum Information and State Key Laboratory of High-Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Engineering and Applied Sciences National Laboratory of Solid State Microstructuresand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China

Optical isolators,the photonic analogs of electronic diodes,are essential for ensuring the unidirectional flow of light in optical systems,thereby mitigating the destabilizing effects of back ***-film lithium niobate(TFLN),hailed as“the silicon of photonics,”has emerged as a pivotal material in the realm of chip-scale nonlinear optics,propelling the demand for compact optical *** report a breakthrough in the development of a fully passive,integrated optical isolator on the TFLN platform,leveraging the Kerr effect to achieve an impressive 10.3 dB of isolation with a minimal insertion loss of 1.87 *** theoretical simulations have demonstrated that our design,when applied to a microring resonator with a Q factor of 5×10^(6),can achieve 20 dB of isolation with an input power of merely 8 *** advancement underscores the immense potential of lithium niobate-based Kerr-effect isolators in propelling the integration and application of high-performance on-chip lasers,heralding a new era in integrated photonics.

关键词： thin-film lithium niobate Kerr effect optical isolator

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Towards Privacy-Aware Causal Structure Learning in Federated Setting

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IEEE Transactions on Big Data 2023年第6期9卷 1525-1535页

作者： Huang, Jianli Guo, Xianjie Yu, Kui Cao, Fuyuan Liang, Jiye Intelligent Interconnected Systems Laboratory of Anhui Province School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University Taiyuan030006 China

Causal structure learning has been extensively studied and widely used in machine learning and various applications. To achieve an ideal performance, existing causal structure learning algorithms often need to centralize a large amount of data from multiple data sources. However, in the privacy-preserving setting, it is impossible to centralize data from all sources and put them together as a single dataset. To preserve data privacy, federated learning as a new learning paradigm has attached much attention in machine learning in recent years. In this paper, we study a privacy-aware causal structure learning problem in the federated setting and propose a novel federated PC (FedPC) algorithm with two new strategies for preserving data privacy without centralizing data. Specifically, we first propose a novel layer-wise aggregation strategy for a seamless adaptation of the PC algorithm into the federated learning paradigm for federated skeleton learning, then we design an effective strategy for learning consistent separation sets for federated edge orientation. The extensive experiments validate that FedPC is effective for causal structure learning in federated learning setting. © 2023 IEEE.

关键词： Big data

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Transmittance Spectrum Asymmetry by Photonic Crystals with Vertical Symmetry Breaking 16

Transmittance Spectrum Asymmetry by Photonic Crystals with V...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhu, Zhaoxiang Li, Jiaqi Gu, Xin Liang, Zhouxin Wang, Bo Lin, Yuhang Chen, Yujie State Key Laboratory of Optoelectronic Materials and Technologies Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Sun Yat-sen University Guangzhou510275 China

ISBN: (纸本)9798350372076

关键词： Photonic crystals

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Ultraviolet photodetectors based on ferroelectric depolarization field

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Journal of Energy Chemistry 2023年第2期77卷 487-498,I0013页

作者： Xiaoyu Zhou Qingqing Ke Silin Tang Jilong Luo Zihan Lu School of Microelectronics Science and Technology Sun Yat-sen UniversityZhuhai 519082GuangdongChina Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen UniversityZhuhai 519082GuangdongChina

Ultraviolet(UV)photodetectors are extensively adopted in the fields of the Internet of Things,optical communications and ***,with broadening the application scope of UV photodetectors,developing integrated devices with more functionalities rather than basic photo-detecting ability are highly required and have been triggered ever-growing interest in scientific and industrial *** thin films have become a potential candidate in the field of UV detection due to their wide bandgap and unique photovoltaic ***,ferroelectric thin films perform excellent dielectric,piezoelectric,pyroelectric,acousto-optic effects,etc.,which can satisfy the demand for the diversified development of UV *** this review,according to the different roles of ferroelectric thin films in the device,the UV photodetectors based on ferroelectric films are classified into ferroelectric depolarization field driven type,ferroelectric depolarization field and built-in electric field co-driven type,and ferroelectric field enhanced *** three types of ferroelectric UV photodetectors have great potential and are expected to promote the development of a new generation of UV detection *** the end of the paper,the advantages and challenges of three types of ferroelectric UV photodetectors are summarized,and the possible development direction in the future is proposed.

关键词： UV photodetector Ferroelectric Thin film Depolarization field Built-in electric field

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Broadband Phase-Polarization Co-Modulated Dielectric Metasurface for Polarization-Independent LCoS Device 16

Broadband Phase-Polarization Co-Modulated Dielectric Metasur...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Li, Jiaqi Gu, Xin Zhu, Zhaoxiang Liang, Zhouxin Lin, Yuhang Wang, Bo Chen, Yujie School of Electronics and Information Technology Sun Yat-sen University State Key Laboratory of Optoelectronic Materials and Technologies Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Guangzhou510275 China

We demonstrate the broadband phase-polarization co-modulated dielectric metasurface towards polarization-independent liquid crystal on silicon (PI-LCoS) device across C+L telecommunication band, which is essential for... 详细信息

ISBN: (纸本)9798350372076

关键词： Dielectric devices

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Neural RAPT: deep learning-based pitch tracking with prior algorithmic knowledge instillation

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International Journal of Speech technology 2023年第4期26卷 999-1015页

作者： Wang, Kai Liu, Jingjing Peng, Yizhou Huang, Hao School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Provincial Key Laboratory of Multi-lingual Information Technology Xinjiang University Urumqi830017 China

The task of estimating the fundamental frequency of an audio signal, also known as pitch tracking, has been a long-standing research area in speech signal processing. Recently, there has been a growing interest in data-driven pitch tracking methods that leverage deep learning technologies. However, deep learning-based pitch tracking models often neglect the methodologies employed in well-established signal processing-based pitch tracking algorithms, which incorporate valuable prior knowledge. Motivated by this, we propose Neural RAPT, an interpretable neural network-based pitch tracking model that incorporates signal processing knowledge from RAPT. The proposed model consists of a front-end module and a back-end module. The front-end module adopts the U-Net structure, which inherently involves downsampling and upsampling processes similar to RAPT. To enhance the U-Net, we introduce a neural autocorrelation function (ACF) module using masked CNN, along with a normalization layer that models the sample pair-wise product in the normalized cross-correlation function (NCCF). The back-end module is based on the Transformer architecture. The model is evaluated by pitch tracking experiments on the PTDB-TUG database and noisy mixtures with the NOISEX-92 database at different SNRs. The experimental results demonstrate that incorporating algorithmic knowledge into the model design leads to improved performance. The proposed model inherits the advantages of high accuracy from traditional pitch tracking algorithms, while also benefiting from the noise robustness offered by neural network-based methods. Consequently, our model exhibits superiority over existing deep learning-based pitch tracking methods. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Deep learning

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Low power consumption reduced state and transition MLSE in optical interconnects

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Science China(information Sciences) 2023年第10期66卷 325-326页

作者： Weihao NI Fan LI Wei WANG Zhibin LUO Xingwen YI Yi CAI Zhaohui LI School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network Suzhou Key Laboratory of Advanced Optical Communication Network Technology Soochow University

Intensity modulation/direct detection(IM/DD) optical fiber communication system is an appropriate candidate for optical interconnect applications due to its low cost and low power consumption characteristics [1]. 4-level pulse amplitude modulation(PAM-4) is widely discussed in optical interconnects due to its simpler transceiver configuration and implementation [2].

关键词： Optical interconnects

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An Evolutionary Multitasking Algorithm for Efficient Multiobjective Recommendations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第3期6卷 518-532页

作者： Tian, Ye Ji, Luke Hu, Yiwei Ma, Haiping Wu, Le Zhang, Xingyi Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei230029 China

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired metaheuristics have been successfully applied to recommender systems and amply demonstrated effectiveness, in particular, for multiobjective recommendation. Owing to the population-based search paradigm, these algorithms can produce a number of recommendation lists, making diverse tradeoffs between multiple metrics and meeting the requirements of accuracy, novelty, diversity, and other user preferences. However, these algorithms are criticized for the low efficiency of the optimization process, especially when the number of users is large. To address this issue, this article proposes an evolutionary multitasking-based recommendation method, where each task corresponds to a user and all the tasks are optimized simultaneously, thus highly improving the efficiency of recommendation. To enhance the convergence speed, all the users are divided into multiple populations according to the similarity between their preferences, where each population evolves with internal knowledge transfer between users, and all the populations evolve with external knowledge transfer between populations. Experimental results on various datasets verify that the proposed method can better balance between multiple metrics than classical and deep neural network-based recommendation methods and exhibits significantly higher efficiency than evolutionary multiobjective optimization-based recommendation methods. © 2024 IEEE. All rights reserved.

关键词： Multiobjective optimization

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AES-AUDIO: An Encryption Scheme for Audio Supporting Differentiated Decryption

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IEEE Transactions on Multimedia 2025年 27卷 2268-2280页

作者： Zhao, Ruoyu Zhang, Yushu Ji, Junhao Yi, Shuang Wen, Wenying Lan, Rushi Jiangxi University of Finance and Economics School of Computer and Artificial Intelligence Nanchang330013 China Jiangxi Provincial Key Laboratory of Multimedia Intelligent Processing Nanchang330013 China Southwest University of Political Science and Law Criminal Investigation School Chongqing401120 China Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China Guilin University of Electronic Technology Guangxi Key Laboratory of Trusted Software Guilin541004 China

In this paper, we propose an audio encryption scheme that supports differentiated decryption, called AES-AUDIO, in which an audio only needs to be encrypted once and can be decrypted into different resolutions as needed. First, we design four security levels, confidential, harsh, noisy, and clear, based on the audio resolution perceived by human auditory perception. Second, the audio data in decimal floating-point numbers (D-FPNs) are unfolded to 32 bits (B-FPNs). Third, we design a region of interest (RoI) encryption algorithm for the audio with the B-FPN format, where the result preserves some perceptual information as needed. Fourth, we construct the AES-AUDIO scheme based on the RoI encryption algorithm, which allows the audio to be encrypted once and then decrypted into different security levels. It supports changing parameters to alter the perception effect corresponding to the security level. Overall, it achieves a balance between the security and usability of the protected audio. User experiments verify that the audios produced by differential decryption can achieve the expected security levels. Some security tests also yielded excellent results, such as an NSCR value of 1. © 1999-2012 IEEE.

关键词： Encryption algorithms

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Open-vocabulary 3D Semantic Understanding via Affinity Neural Radiance Fields 6

Open-vocabulary 3D Semantic Understanding via Affinity Neura...

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6th International Conference on Next Generation Data-Driven Networks, NGDN 2024

作者： Fan, Yujie Luo, Huan Computer and Data Science Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9798350388374

Three-dimensional semantic understanding using only several multi-view images can largely reduce the communication burden on the network. In addition, while point clouds are extensively studied for 3D scene understanding, utilization of multi-view image data offers rich visual details and texture information. However, challenges persist in lifting 2D semantic features to 3D space and leveraging language for segmentation. Inspired by recent advancements, this paper proposes a method that combines CLIP features and SAM masks to create a feature field capable of segmenting objects via natural language text across 2D multi-view and 3D Gaussian splatting. It offers a promising function for extracting 3D assets for game engines and the metaverse. Our method involves mask generation from video frames, extracting physical scales via RGB Nerf with masks, and organizing hierarchical information for semantic comprehension. In the training process, affinity features maintain scale properties and guide CLIP feature generation with auto weights blending for semantic robustness. A straightforward 3D splatting CLIP feature approach and canonical text methodology enhance query robustness across 2D multi-view and 3D splatting through relevance score calculation based on text CLIP features for inference. Experimental results demonstrate promising improvements in semantic understanding of 3D scenes. © 2024 IEEE.

关键词： Semantic Segmentation

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