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Optimal control of linear Gaussian quantum systems via quantum learning control

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arXiv 2024年

作者： Liu, Yu-Hong Zeng, Yexiong Tan, Qing-Shou Dong, Daoyi Nori, Franco Liao, Jie-Qiao Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Theoretical Quantum Physics Laboratory Cluster for Pioneering Research RIKEN Wakoshi Saitama351-0198 Japan Quantum Computing Center RIKEN Wakoshi Saitama351-0198 Japan Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communication College of Physics and Electronics Hunan Institute of Science and Technology Yueyang414000 China School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia Department of Physics The University of Michigan Ann ArborMI48109-1040 United States Institute of Interdisciplinary Studies Hunan Normal University Changsha410081 China

Efficiently controlling linear Gaussian quantum (LGQ) systems is a significant task in both the study of fundamental quantum theory and the development of modern quantum technology. Here, we propose a general quantum-learning-control method for optimally controlling LGQ systems based on the gradient-descent algorithm. Our approach flexibly designs the loss function for diverse tasks by utilizing first- and second-order moments that completely describe the quantum state of LGQ systems. We demonstrate both deep optomechanical cooling and large optomechanical entanglement using this approach. Our approach enables the fast and deep ground-state cooling of a mechanical resonator within a short time, surpassing the limitations of sideband cooling in the continuous-wave driven strong-coupling regime. Furthermore, optomechanical entanglement could be generated remarkably fast and surpass several times the corresponding steady-state entanglement, even when the thermal phonon occupation reaches one hundred. This work will not only broaden the application of quantum learning control, but also open an avenue for optimal control of LGQ systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Cooling

Master equations and quantum trajectories for squeezed wave packets

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Physical Review A 2022年第2期105卷 023721-023721页

作者： Jonathan A. Gross Ben Q. Baragiola T. M. Stace Joshua Combes Institut Quantique Université de Sherbrooke Sherbrooke Quebec Canada J1K 2R1 Center for Quantum Information and Control University of New Mexico Albuquerque New Mexico 87131-0001 USA Yukawa Institute for Theoretical Physics Kyoto University Kitashirakawa Oiwakecho Sakyo-ku Kyoto 606-8502 Japan Centre for Quantum Computation and Communication Technology School of Science RMIT University Melbourne Victoria 3000 Australia ARC Centre for Engineered Quantum System Department of Physics University of Queensland Brisbane Queensland 4072 Australia Department of Electrical Computer and Energy Engineering University of Colorado Boulder Boulder Colorado 80309 USA

The interaction between matter and squeezed light has mostly been treated within the approximation that the field-correlation time is small. Methods for treating squeezed light with more general correlations currently involve explicitly modeling the systems producing the light. We develop a general purpose input-output theory for a particular form of narrowband squeezed light, a squeezed wave-packet mode, that only concerns the statistics of the squeezed field and the shape of the wave packet. This formalism allows us to derive the input-output relations and the master equation. We also consider detecting the scattered field using photon counting and homodyne measurements, which necessitates the derivation of the stochastic master equation. The non-Markovian nature of the field manifests itself in the master equation as a coupled hierarchy of equations. We illustrate these with consequences for the decay and resonance fluorescence of two-level atoms in the presence of such fields.

关键词： Open quantum systems Squeezing of quantum noise Stochastic processes

Parallel naive Bayes algorithm for large-scale Chinese text classification based on spark

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Journal of Central South University 2019年第1期26卷 1-12页

作者： LIU Peng ZHAO Hui-han TENG Jia-yu YANG Yan-yan LIU Ya-feng ZHU Zong-wei Internet of Things Perception Mine Research Centre China University of Mining and Technology National and Local Joint Engineering Laboratory of Internet Application Technology on Mine School of Information and Control Engineering China University of Mining and Technology Communication Division NARI Technology Co. Ltd. Suzhou Institute of University of Science and Technology of China

The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these *** order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big *** algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also *** test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and ***,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.

关键词： Chinese text classification naive Bayes spark hadoop resilient distributed dataset parallelization

A Spectrum Status Duration Prediction Method Based on Homotopy Theory for UAV communication

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A Spectrum Status Duration Prediction Method Based on Homoto...

International Conference on Computer and communications (ICCC)

作者： Tao Zhou Shan Luo Peixiang Zheng Rongping Lin School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

With the development of wireless communication technology, a large number of spectrum resources are occupied and become increasingly scarce. If drones want to communicate, they need to share spectrum with others. The method of spectrum prediction in cognitive radio can efficiently achieve this. The traditional spectrum status duration prediction method based on the non-stationary hidden Markov model only predict the duration of one fixed geographic location and cannot meet the requirement of UAV's communications. We intend to apply the homotopy theory to the non-stationary hidden Markov model to obtain the spectrum status duration of different locations so that it can apply to UAV's communications. We also conducted experiments to predict the duration of the spectrum status at different locations. The experimental results show that our model can work well.

关键词： Computational modeling Conferences Hidden Markov models Predictive models Markov processes Cognitive radio Drones

Energy Consumption Optimal Design of Power Grid Inspection Trajectory for UAV Mobile Edge Computing Node

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Energy Consumption Optimal Design of Power Grid Inspection T...

Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Yu Zhang Junfeng Li Litong Zhang Na Zhao Wei Tang Rui Wang Ke Xiong Institute of Economics and Energy Supply and Demand State Grid Energy Research Institute Co. Ltd. Beijing China State Grid Corporation of China Beijing China Network and Information Security Research Center Research Institute of China United Network Communication Co. Ltd. Beijing China School of Telecommunications Engineering Beijing Polytechnic Beijing China School of Automatic Control Engineering Liaoning Radio and TV University Shenyang China School of Computer and Information Technology Beijing Jiaotong University Beijing China

The inspection of transmission equipment by UAV has become an indispensable daily operation and maintenance method for overhead transmission lines. The passive sensors installed on the power transmission equipment needs to complete all its data calculation tasks within a given period of time, and needs to store a certain amount of energy to maintain its normal operation afterwards. During the inspection work, the UAV provides energy for the sensor device, and calculates the data uploaded by the sensor device, and returns the result to the sensor after the calculation is completed. Aiming at the problem of limited UAV energy and short working time, this paper proposes a optimization problem through joint optimization of UAV trajectory, sensor data unloading, sensor wireless energy transmission and other factors. According to convex optimization theory, this optimization problem can be solved based on successive convex approximation (SCA) theory. Compared with the benchmark algorithm, the UAV obtained by the optimization plan in this paper has the lowest flight energy consumption, and as time increases, the advantages of the optimization plan in this paper become more obvious. The algorithm proposed in this paper effectively reduces the energy consumption of the UAV during the execution of the mission and improves the efficiency of the UAV inspection.

关键词： Energy consumption Computational modeling Wireless power transfer Inspection Approximation algorithms Sensors Trajectory

On the Secrecy of UAV Systems With Linear Trajectory

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arXiv 2020年

作者： Pan, Gaofeng Lei, Hongjiang An, Jianping Zhang, Shuo Alouini, Mohamed-Slim School of Information and Electronics Engineering Beijing Institute of Technology Beijing100081 China Thuwal23955-6900 Saudi Arabia School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Shannxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and Telecommunications Xi’anShaanxi710121 China School of Information and Electronics Engineering Beijing Institute of Technology Beijing100081 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China Beijing Aerospace Automatic Control Institute Beijing100854 China Thuwal23955-6900 Saudi Arabia

By observing the fact that moving in a straight line is a common flying behavior of unmanned aerial vehicles (UAVs) in normal applications, e.g., power line inspections, and air patrols along with highway/streets/borders, in this paper we investigate the secrecy outage performance of a UAV system with linear trajectory, where a UAV (S) flies in a straight line and transmits its information over the downlink to a legitimate receiver (D) on the ground while an eavesdropping UAV (E) trying to overhear the information delivery between S and D. Meanwhile, some information is delivered to S over the uplink from D, such as commanding messages to control S’s detecting operations, which can also be eavesdropped by E. The locations of S, D, and E are randomly distributed. We first characterize the statistical characteristics (including cumulative distribution functions and probability density function) of the received signal-to-noise ratio over both downlink and uplink, and then the closed-form analytical Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

Progressive Inertial Poser: Progressive Real-Time Kinematic Chain Estimation for 3D Full-Body Pose from Three IMU Sensors

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IEEE Transactions on Instrumentation and measurement 2025年 74卷

作者： Zhu, Zunjie Zhao, Yan Hu, Yihan Wang, Guoxiang Qiu, Hai Zheng, Bolun Yan, Chenggang Xu, Feng Hangzhou Dianzi University School of Communication Engineering Hangzhou 323000 China Wenzhou Institute of Hangzhou Dianzi University Key Laboratory of Micro-nano Sensing and IoT of Wenzhou Wenzhou 325038 China Tiangong University School of Control Science and Engineering Tianjin 300387 China Lishui University College of Business Lishui 310018 China Costar Intelligent Optoelectronics Technology Co. Ltd China Hangzhou Dianzi University School of Automation Hangzhou 323000 China Macao Polytechnic University Faculty of Applied Sciences 999078 Macao Tsinghua University School of software and BNRist Beijing 100084 China

The motion capture system that supports full-body virtual representation is of key significance for virtual reality. Compared to vision-based systems, full-body pose estimation from sparse tracking signals is not limited by environmental conditions or recording range. However, previous works either face the challenge of wearing additional sensors on the pelvis and lower-body or rely on external visual sensors to obtain global positions of key joints. To improve the practicality of the technology for virtual reality applications, we estimate full-body poses using only inertial data obtained from three Inertial measurement Unit (IMU) sensors worn on the head and wrists, thereby reducing the complexity of the hardware system. In this work, we propose a method called Progressive Inertial Poser (ProgIP) for human pose estimation, which combines neural network estimation with a human dynamics model, considers the hierarchical structure of the kinematic chain, and employs a multi-stage progressive network estimation with increased depth to reconstruct full-body motion in real time. The encoder combines Transformer Encoder and bidirectional LSTM (TE-biLSTM) to flexibly capture the temporal dependencies of the inertial sequence, while the decoder based on multi-layer perceptrons (MLPs) transforms high-dimensional features and accurately projects them onto Skinned Multi-Person Linear (SMPL) model parameters. Quantitative and qualitative experimental results on multiple public datasets show that our method outperforms state-of-the-art methods with the same inputs, and is comparable to recent works using six IMU sensors. © 1963-2012 IEEE.

关键词： full-body virtual representation IMU sensors kinematic chain motion capture neural network progressive estimation virtual reality

Differential Reflecting Modulation for Reconfigurable Intelligent Surface Based communications

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arXiv 2020年

作者： Guo, Shuaishuai Ye, Jia Zhang, Peng Zhang, Haixia Alouini, Mohamed-Slim Shandong Provincial Key Laboratory of Wireless Communication Technologies School of Control Science and Engineering Shandong University Jinan250061 China Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia School of Computer Engineering Weifang University Weifang261061 China

Reconfigurable intelligent surface (RIS) based communications have emerged as a new paradigm. This letter proposes a differential reflecting modulation (DRM) scheme for RIS based communication systems. In DRM, information bits are jointly carried by the activation permutations of the reflecting patterns and the phases of the transmitted signals, leading to that DRM can work without any channel state information (CSI) at the transmitter, RIS or receiver. In other words, DRM can release the intricate and resource-consuming channel estimation in the transmission process. Simulation results show that the proposed DRM pays acceptable SNR penalty compared to non-differential modulation scheme with coherent detection. Copyright © 2020, The Authors. All rights reserved.

关键词： Modulation

Progressive Inertial Poser: Progressive Real-Time Kinematic Chain Estimation for 3D Full-Body Pose from Three IMU Sensors

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arXiv 2025年

作者： Zhu, Zunjie Zhao, Yan Hu, Yihan Wang, Guoxiang Qiu, Hai Zheng, Bolun Yan, Chenggang Xu, Feng School of Communication Engineering Hangzhou Dianzi University Hangzhou323000 China Key Laboratory of Micro-nano Sensing and IoT of Wenzhou Wenzhou Institute of Hangzhou Dianzi University Wenzhou325038 China School of Control Science and Engineering Tiangong University Tianjin300387 China College of Business Lishui University Lishui310018 China Costar Intelligent Optoelectronics Technology Co. Ltd China School of Automation Hangzhou Dianzi University Hangzhou323000 China Faculty of Applied Sciences Macao Polytechnic University 999078 China School of software and BNRist Tsinghua University Beijing100084 China

关键词： Virtual reality