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Dual-channel quantum meta-hologram for display

Advanced Photonics Nexus 2024年第1期3卷 86-92页

作者： Yubin Fan Hong Liang Yuhan Wang Shufan Chen Fangxing Lai Mu Ku Chen Shumin Xiao Jensen Li Din Ping Tsai City University of Hong Kong Department of Electrical EngineeringHong KongChina City University of Hong Kong Centre for BiosystemsNeuroscienceand NanotechnologyHong KongChina City University of Hong Kong The State Key Laboratory of Terahertz and Millimeter WavesHong KongChina The Hong Kong University of Science and Technology Department of PhysicsHong KongChina The Hong Kong University of Science and Technology IAS Center for Quantum TechnologiesHong KongChina Harbin Institute of Technology(Shenzhen) Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information SystemGuangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsShenzhenChina Pengcheng Laboratory ShenzhenChina

Quantum technologies rely on creating and manipulating entangled sources,which are essential for quantum information,communication,and *** integrating quantum technologies and all-dielectric metasurfaces,the performance of miniature display devices can be enhanced to a higher *** display technology,such as virtual reality display,has achieved original commercial success,and was initially applied to immersive games and interactive *** the consumer market has quickly adopted this technology,several areas remain for improvement,including concerns around bulkiness,dual-channel display,and noise ***,we experimentally realize a quantum meta-hologram concept demonstration of a miniature *** fabricate an ultracompact meta-hologram based on 1μm thick titanium dioxide(TiO_(2)).The meta-hologram can be remotely switched with heralding technique and is robust against noise with the quantum entangled *** platform can alter the miniature display channel by manipulating heralding photons’polarization,removing speckles and multiple reflective light noise,improving imaging contrast,and potentially decreasing device *** contrast increases from 0.36 dB under speckle noise influences to 6.8 dB in quantum correlation *** approach has the potential to miniaturize quantum displays and quantum communication devices.

关键词： quantum meta-hologram display metasurface dual channel

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Unijunction Transistor on Silicon-On-Insulator Substrate 15

Unijunction Transistor on Silicon-On-Insulator Substrate

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15th IEEE International Conference on Solid-state and Integrated Circuit Technology, ICSICT 2020

作者： Chen, Y.X. Liu, J. Xiao, K. Zaslavsky, A. Cristoloveanu, S. Liu, F.Y. Li, B. Wan, J. State Key Lab of ASIC and System School of Information Science and Engineering Fudan University Shanghai China Brown University Department of Physics and School of Engineering ProvidenceRI02912 United States IMEP-LAHC INP-Grenoble/Minatec CS 50257 Grenoble38016 France Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China

ISBN: (纸本)9781728162355

A unijunction transistor based on fully-depleted silicon-on-insulator substrate is proposed. The device structure is similar to a junction field effect transistor. By conducting the TCAD simulation, we observe sharp switching and large hysteresis in emitter current-emitter voltage curves with the turn-on voltage linearly controlled by the second base voltage. The operation of the device is mainly determined by the emitter-channel PN junction, which is induced by the backgate voltage. The impact of the backgate voltage on the electrical characteristics is analyzed by changes in the channel potential. © 2020 IEEE.

关键词： Silicon on insulator technology

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Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

arXiv

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arXiv 2021年

作者： Li, Longyuan Zhang, Jihai Yan, Junchi Jin, Yaohui Zhang, Yunhao Duan, Yanjie Tian, Guangjian MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China State Key Lab of Advanced Optical Communication System and Network Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Huawei Noah’s Ark Lab China

Time-series is ubiquitous across applications, such as transportation, finance and healthcare. Time-series is often influenced by external factors, especially in the form of asynchronous events, making forecasting difficult. However, existing models are mainly designated for either synchronous time-series or asynchronous event sequence, and can hardly provide a synthetic way to capture the relation between them. We propose Variational Synergetic Multi-Horizon Network (VSMHN), a novel deep conditional generative model. To learn complex correlations across heterogeneous sequences, a tailored encoder is devised to combine the advances in deep point processes models and variational recurrent neural networks. In addition, an aligned time coding and an auxiliary transition scheme are carefully devised for batched training on unaligned sequences. Our model can be trained effectively using stochastic variational inference and generates probabilistic predictions with Monte-Carlo simulation. Furthermore, our model produces accurate, sharp and more realistic probabilistic forecasts. We also show that modeling asynchronous event sequences is crucial for multi-horizon time-series forecasting. © 2021, CC BY.

关键词： Time series

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Towards ISAC-Empowered Vehicular Networks: Framework, Advances, and Opportunities

arXiv

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arXiv 2023年

作者： Du, Zhen Liu, Fan Li, Yunxin Yuan, Weijie Cui, Yuanhao Zhang, Zenghui Masouros, Christos Ai, Bo School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Connected and autonomous vehicle (CAV) networks face several challenges, such as low throughput, high latency, and poor localization accuracy. These challenges severely impede the implementation of CAV networks for immersive metaverse applications and driving safety in future 6G wireless networks. To alleviate these issues, integrated sensing and communications (ISAC) is envisioned as a game-changing technology for future CAV networks. This article presents a comprehensive overview on the application of ISAC techniques in vehicle-to-infrastructure (V2I) networks. We cover the general system framework, representative advances, and a detailed case study on using the 5G New Radio (NR) waveform for sensing-assisted communications in V2I networks. Finally, we highlight open problems and opportunities in the field. Copyright © 2023, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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Distributed machine learning for wireless communication networks: Techniques, architectures, and applications

arXiv

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arXiv 2020年

作者： Hu, Shuyan Chen, Xiaojing Ni, Wei Hossain, Ekram Wang, Xin State Key Laboratory of ASIC and System School of Information Science and Technology Fudan University Shanghai200433 China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China SydneyNSW2122 Australia Department of Electrical and Computer Engineering University of Manitoba WinnipegMBR3T 5V6 Canada State Key Laboratory of ASIC and System Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai200433 China

Distributed machine learning (DML) techniques, such as federated learning, partitioned learning, and distributed reinforcement learning, have been increasingly applied to wireless communications. This is due to improved capabilities of terminal devices, explosively growing data volume, congestion in the radio interfaces, and increasing concern of data privacy. The unique features of wireless systems, such as large scale, geographically dispersed deployment, user mobility, and massive amount of data, give rise to new challenges in the design of DML techniques. There is a clear gap in the existing literature in that the DML techniques are yet to be systematically reviewed for their applicability to wireless systems. This survey bridges the gap by providing a contemporary and comprehensive survey of DML techniques with a focus on wireless networks. Specifically, we review the latest applications of DML in power control, spectrum management, user association, and edge cloud computing. The optimality, scalability, convergence rate, computation cost, and communication overhead of DML are analyzed. We also discuss the potential adversarial attacks faced by DML applications, and describe state-of-the-art countermeasures to preserve privacy and security. Last but not least, we point out a number of key issues yet to be addressed, and collate potentially interesting and challenging topics for future research. Copyright © 2020, The Authors. All rights reserved.

关键词： Data privacy

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Cell-Free Massive MIMO with Normalized Conjugate Beamforming and Channel Non-Reciprocities 13

Cell-Free Massive MIMO with Normalized Conjugate Beamforming...

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13th International Conference on Wireless communications and Signal Processing, WCSP 2021

作者： Zhang, Yao Xia, Wenchao Zhu, Yongxu Zheng, Gan Gao, Feifei Zhejiang Normal University College of Physics and Electronic Information Engineering Jinhua321004 China Nanjing University of Posts and Telecommunications Department of Wireless Communication Key Lab of Jiangsu Province Nanjing210003 China London South Bank University Division of Computer Science and Informatics London United Kingdom Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University LeicestershireLE11 3TU United Kingdom Institute for Artificial Intelligence Tsinghua University State Key Lab of Intelligent Technologies and Systems Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China

ISBN: (纸本)9781665407854

This paper focuses on a generalized downlink cell-free massive multiple-input multiple-output (CF-mMIMO) system with normalized conjugate beamforming (NCB) and channel non-reciprocities, assuming the access points (APs) are equipped with low-resolution digital-to-analog converters (DACs). Specifically, the channel non-reciprocities consist of the amplitude and phase non-reciprocities at the APs and user equipments. Closed-form expressions of the achievable sum-rates are derived for evaluating the impacts of channel non-reciprocities and DAC resolutions and comparing against the conjugate beamforming (CB) counterpart. Simulation results reveal that the downlink sum-rates are immune to the amplitude non-reciprocity of transceivers but strongly sensitive to the AP phase non-reciprocity. In particular, a small degree of AP phase non-reciprocity can result in substantial rate degradations. Besides, 5-bit DACs are enough in CF-mMIMO systems to approach the same sum-rates as CF-mMIMO systems with high-resolution DACs. Moreover, the NCB scheme outperforms the CB scheme in terms of the downlink sum-rates for both reciprocal and non-reciprocal channels. © 2021 IEEE.

关键词： Beamforming

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Intelligent Multi-Modal Sensing-communication Integration: Synesthesia of Machines

arXiv

引用

arXiv 2023年

作者： Cheng, Xiang Zhang, Haotian Zhang, Jianan Gao, Shijian Li, Sijiang Huang, Ziwei Bai, Lu Yang, Zonghui Zheng, Xinhu Yang, Liuqing The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China The Samsung Semiconductor Samsung SoC Research and Development Lab San DiegoCA92121 United States Shandong University Jinan250100 China Guangzhou510000 China Guangzhou510000 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

In the era of sixth-generation (6G) wireless communications, integrated sensing and communications (ISAC) is recognized as a promising solution to upgrade the physical system by endowing wireless communications with sensing capability. Existing ISAC is mainly oriented to static scenarios with radio-frequency (RF) sensors being the primary participants, thus lacking a comprehensive environment feature characterization and facing a severe performance bottleneck in dynamic environments. To date, extensive surveys on ISAC have been conducted but are limited to summarizing RF-based radar sensing. Currently, some research efforts have been devoted to exploring multi-modal sensing-communication integration but still lack a comprehensive review. To fill the gap, we embark on an initial endeavor with the goal of establishing a unified framework of intelligent multi-modal sensing-communication integration by generalizing the concept of ISAC and providing a comprehensive review under this framework. Inspired by the human synesthesia, the so-termed Synesthesia of Machines (SoM) gives the clearest cognition of such an intelligent integration and details its paradigm for the first time. We commence by justifying the necessity and potential of the new paradigm. Subsequently, we offer a rigorous definition of SoM and zoom into the detailed paradigm, which is summarized as three operational modes realizing the integration. To facilitate SoM research, we overview the prerequisite of SoM research, that is, mixed multi-modal (MMM) datasets, and introduce our work. Built upon the MMM datasets, we introduce the mapping relationships between multi-modal sensing and communications, and discuss how channel modeling can be customized to support the exploration of such relationships. Afterward, aiming at giving a comprehensive survey on the current research status of multi-modal sensing-communication integration, we cover the technological review on SoM-enhance-based and SoM-concert-based app

关键词： Beamforming

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Cooling-aware resource allocation and load management for mobile edge computing systems

arXiv

引用

arXiv 2020年

作者： Chen, Xiaojing Lu, Zhouyu Ni, Wei Wang, Xin Wang, Feng Zhang, Shunqing Xu, Shugong Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China SydneyNSW2122 Australia State Key Laboratory of ASIC and System Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai200433 China School of Information Engineering Guangdong University of Technology Guangzhou510006 China

Driven by explosive computation demands of Internet of Things (IoT), mobile edge computing (MEC) provides a promising technique to enhance the computation capability for mobile users. In this paper, we propose a joint resource allocation and load management mechanism in an MEC system with wireless power transfer (WPT), by jointly optimizing the transmit power for WPT, the local/edge computing load, the offloading time, and the frequencies of the central processing units (CPUs) at the access point (AP) and the users. To achieve an energy-efficient and sustainable WPT-MEC system, we minimize the total energy consumption of the AP, while meeting computation latency requirements. Cooling energy which is non-negligible, is taken into account in minimizing the energy consumption of the MEC system. By rigorously orchestrating the state-of-the-art optimization techniques, we design an iterative algorithm and obtain the optimal solution in a semi-closed form. Based on the solution, interesting properties and insights are summarized. Extensive numerical tests show that the proposed algorithm can save up to 90.4% the energy of existing benchmarks. Copyright © 2020, The Authors. All rights reserved.

关键词： Convex optimization

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Hybrid MMSE Beamforming for Multiuser Millimeter Wave communication systems

arXiv

引用

arXiv 2019年

作者： Cong, Jiaqi Lin, Tian Zhu, Yu State Key Laboratory of ASIC and System Department of Communication Science and Engineering Fudan University Shanghai China

This letter investigates the hybrid analog and digital beamforming (HBF) design for multiuser millimeter wave (mmWave) communication systems based on the minimum mean square error (MMSE) criterion. Using the alternating minimization method, the hybrid precoder of the base station (BS) and the hybrid combiners of the users are alternatively optimized. It is shown that both the optimized digital precoder of the BS and the digital combiners of the users have closed-form expressions, and their corresponding analog ones can be efficiently obtained via generalized eigen-decomposition. Simulation results show that the proposed MMSE HBF scheme has fast convergence and performs close to the fully digital beamforming. Copyright © 2019, The Authors. All rights reserved.

关键词： Mean square error

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

引用

arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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