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Multimode optomechanical cooling via general dark-mode control

Physical Review A 2022年第1期106卷 013526-013526页

作者： Jian Huang Deng-Gao Lai Cheng Liu Jin-Feng Huang Franco Nori Jie-Qiao Liao 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 and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 China Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan RIKEN Center for Quantum Computing 2-1 Hirosawa Wako-shi Saitama 351-0198 Japan Physics Department University of Michigan Ann Arbor Michigan 48109-1040 USA

The dark-mode effect is a stubborn obstacle for ground-state cooling of multiple degenerate mechanical modes optomechanically coupled to a common cavity-field mode. Here we propose an auxiliary-cavity-mode method for simultaneous ground-state cooling of two degenerate or near-degenerate mechanical modes by breaking the dark mode. We find that the introduction of the auxiliary cavity mode not only breaks the dark-mode effect, but also provides a new cooling channel to extract the thermal excitations stored in the dark mode. Moreover, we study the general physical-coupling configurations for breaking the dark mode in a generalized network-coupled four-mode optomechanical system consisting of two cavity modes and two mechanical modes. We find the analytical dark-mode-breaking condition in this system. This method is general and it can be generalized to break the dark-mode effect and to realize the simultaneous ground-state cooling in a multiple-mechanical-mode optomechanical system. We also demonstrate the physical mechanism behind the dark-mode breaking by studying the breaking of dark-state effect in the N−type four-level atomic system. Our results not only provide a general method to control various dark-mode and dark-state effects in physics, but also present an opportunity to the study of macroscopic quantum phenomena and applications in multiple-mechanical-resonator systems.

关键词： Optomechanics Quantum optics

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Tunable coupling of a quantum phononic resonator to a transmon qubit with flip-chip architecture

arXiv

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arXiv 2024年

作者： Ruan, Xinhui Li, Li Liang, Guihan Zhao, Silu Wang, Jia-Heng Bu, Yizhou Chen, Bingjie Song, Xiaohui Li, Xiang Zhang, He Wang, Jinzhe Zhao, Qianchuan Xu, Kai Fan, Heng Liu, Yu-Xi Zhang, Jing Peng, Zhihui Xiang, Zhongcheng Zheng, Dongning Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China 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 School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Integrated Circuits Tsinghua University Beijing100084 China Hefei National Laboratory Hefei230088 China School of Automation Science and Engineering Xi'an Jiaotong University Xi’an710049 China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi’an710049 China CAS Center for Excellence in Topological Quantum Computation School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China

A hybrid system with tunable coupling between phonons and qubits shows great potential for advancing quantum information processing. In this work, we demonstrate strong and tunable coupling between a surface acoustic wave (SAW) resonator and a transmon qubit based on galvanic-contact flip-chip technique. The coupling strength varies from 2π×7.0 MHz to -2π×20.6 MHz, which is extracted from different vacuum Rabi oscillation frequencies. The phonon-induced ac Stark shift of the qubit at different coupling strengths is also shown. Our approach offers a good experimental platform for exploring quantum acoustics and hybrid systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Hybrid systems

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A Real-Time CAN-CAN Gateway with Tight Latency Analysis and Targeted Priority Assignment

A Real-Time CAN-CAN Gateway with Tight Latency Analysis and ...

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Real-Time Systems Symposium (RTSS)

作者： Guoqi Xie Haijie Gong Yunbo Han Samarjit Chakraborty Wanli Chang College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Future Network Lab CSIG Tencent China University of North Carolina at Chapel Hill USA University of York UK

ISBN: (数字)9781728183244

ISBN: (纸本)9781728183251

There is a demand in the automotive industry to connect two CAN-based subsystems. The commercial CAN-CAN gateway supports basic message forwarding with no real-time behavior. To address this issue, a new gateway architecture is described, on which we present a novel worst-case latency analysis. Specifically, we bound the arrival of the messages at the gateway, which is then used by the Pointer Reachability Exploration (PRE) to derive the interfering message jobs. Our analysis computes a safe gateway latency tighter than the conventional one applied in CAN. Furthermore, we propose a Targeted Priority Assignment (TPA) algorithm that targets at the priorities assigned at the CAN bus and runs a reordering at the gateway to enhance the schedulability. TPA performs better than DMPO (Deadline Monotonic Priority Ordering), while OPA (Audsley's Optimal Priority Assignment) cannot be applied in this context. Evaluation over real-life and scalable CAN message sets is conducted. The reported analysis and priority assignment algorithm are developed for dynamic use to improve the acceptance ratio and can also be deployed statically to provide timing guarantees. This work can be easily extended to support multiple CAN subsystems.

关键词： Heuristic algorithms Prototypes Computer architecture Logic gates Real-time systems Timing Vehicle dynamics

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Efficient group signature scheme without pairings

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International Journal of network Security 2020年第3期22卷 504-515页

作者： Gu, Ke Liu, Dianxing Yin, Bo School of Computer and Communication Engineering Changsha University of Science and Technology Wangjiali Rd Tianxin district Changsha Hunan Province410114 China Key Laboratory of Network Crime Investigation of Hunan Provincial Colleges Hunan Police Academy Wangjiali Rd Tianxin district Changsha Hunan Province410114 China

Although currently many group signature schemes have been proposed, most of them are constructed on pair-ings. In this paper, we present an efficient group signature scheme without pairings under the model of verifier-local revocation, which is based on the modified EDL signature (first proposed by D. Chaum et al. in Crypto 92). Com-pared with other group signature schemes, the proposed scheme does not employ pairing computation and has the constant signing time and signature size, whose secu-rity can be reduced to the computational Diffie-Hellman (CDH) assumption in the random oracle model. Also, we give a formal security model for group signature and prove that the proposed scheme has the properties of traceabil-ity and anonymity. © 2020 Femto Technique Co., Ltd.

关键词： Authentication

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An Evidence Combination Method based on DBSCAN Clustering

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Computers, Materials & Continua 2018年第11期57卷 269-281页

作者： Kehua Yang Tian Tan Wei Zhang College of Computer Science and Electronic Engineering and Key Laboratory for Embedded and Network Computing of Hunan ProvinceHunan UniversityChangshaHunan410082China Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State UniversityVirginiaBlacksburg24060USA

Dempster-Shafer(D-S)evidence theory is a key technology for integrating uncertain information from multiple ***,the combination rules can be paradoxical when the evidence seriously conflict with each *** the paper,we propose a novel combination algorithm based on unsupervised Density-Based Spatial Clustering of Applications with Noise(DBSCAN)density *** the proposed mechanism,firstly,the original evidence sets are preprocessed by DBSCAN density clustering,and a successfully focal element similarity criteria is used to mine the potential information between the evidence,and make a correct measure of the conflict ***,two different discount factors are adopted to revise the original evidence sets,based on the result of DBSCAN density ***,we conduct the information fusion for the revised evidence sets by D-S combination *** results show that the proposed method can effectively solve the synthesis problem of high-conflict evidence,with better accuracy,stability and convergence speed.

关键词： D-S evidence theory information fusion DBSCAN combination rules

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A deep hashing method based on attention module for image retrieval

A deep hashing method based on attention module for image re...

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International Conference on Intelligent Computation Technology and Automation, ICICTA

作者： Jun Long Xiangxiang Wei Qianqian Qi Ye Wang The School of Computer Science and Engineering Central South University Changsha China Network Resources Management and Trust Evaluation Key Laboratory of Hunan Province Changsha China

Hashing retrieval technique has received widespread attention since its low storage consumption and fast retrieval speed. Image retrieval based on deep hashing method uses image features with high-level semantic information and discriminative expression capabilities. However, there are still some limitations: (1) Compared with the traditional feature vector, the length of the learned hash codes is short, and each bit of the code is -1 or 1, the discrimination capability of feature representation is limited; (2) the existing deep hash algorithms cannot directly learn the discrete hash codes using sign activation function, therefore, they use relaxation-based scheme to learn the hash codes, resulting in a large quantization error. In order to solve the above problems, a deep hashing retrieval algorithm incorporate with attention model is proposed. This algorithm embeds spatial and channel attention models in the feature extraction network, and uses a novel activation function in the hash layer. In addition, a novel triple loss function is further proposed to improve the learning capability of the network. Finally, experimental results on the two benchmark databases, i.e., CIFAR-10 and MINIST datasets, show the effectiveness and superiority compared with the baselines.

关键词： Codes Quantization (signal) Automation Databases Computational modeling Image retrieval Semantics

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Expert consensus on the diagnosis and treatment of solid tumors with BRAF mutations

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The Innovation 2024年第6期5卷 100-116页

作者： Wenxian Wang Bin Lian Chunwei Xu Qian Wang Ziming Li Nan Zheng Aijun Liu Jinpu Yu Wenzhao Zhong Zhijie Wang Yongchang Zhang Jingjing Liu Shirong Zhang Xiuyu Cai Anwen Liu Wen Li Lili Mao Ping Zhan Hongbing Liu Tangfeng Lv Liyun Miao Lingfeng Min Yu Chen Jingping Yuan Feng Wang Zhansheng Jiang Gen Lin Long Huang Xingxiang Pu Rongbo Lin Weifeng Liu Chuangzhou Rao Dongqing Lv Zongyang Yu Xiaoyan Li Chuanhao Tang Chengzhi Zhou Junping Zhang Junli Xue Hui Guo Qian Chu Rui Meng Xuewen Liu Jingxun Wu Rui Zhang Jin Zhou Zhengfei Zhu Yongheng Li Hong Qiu Fan Xia Yuanyuan Lu Xiaofeng Chen Jian Feng Rui Ge Enyong Dai Yu Han Weiwei Pan Fei Pang Xin Huang Meizhen Hu Qing Hao Kai Wang Fan Wu Binbin Song Bingwei Xu Liping Wang Youcai Zhu Li Lin Yanru Xie Xinqing Lin Jing Cai Ling Xu Jisheng Li Xiaodong Jiao Kainan Li Jia Wei Huijing Feng Lin Wang Yingying Du Wang Yao Xuefei Shi Xiaomin Niu Dongmei Yuan Yanwen Yao Jianhui Huang Yue Feng Yinbin Zhang Pingli Sun Hong Wang Mingxiang Ye Dong Wang Zhaofeng Wang Yue Hao Zhen Wang Bin Wan Donglai Lv Shengjie Yang Jin Kang Jiatao Zhang Chao Zhang Wenfeng Li Jianfei Fu Lizhi Wu Shijie Lan Juanjuan Ou Lin Shi Zhanqiang Zhai Yina Wang Bihui Li Zhang Zhang Ke Wang Xuelei Ma Zhongwu Li Zhefeng Liu Nong Yang Lin Wu Huijuan Wang Gu Jin Guansong Wang Jiandong Wang Hubing Shi Meiyu Fang Yong Fang Yuan Li Xiaojia Wang Jing Chen Yiping Zhang Xixu Zhu Yi Shen Shenglin Ma Biyun Wang Yong Song Zhengbo Song Wenfeng Fang Yuanzhi Lu Lu Si Department of Chemotherapy Chinese Academy of Sciences University Cancer Hospital(Zhejiang Cancer Hospital)HangzhouZhejiang 310022P.R.China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Department of Melanoma and SarcomaPeking University Cancer Hospital&InstituteBeijing 100142P.R.China Institute of Cancer and Basic Medicine(ICBM) Chinese Academy of SciencesHangzhouZhejiang 310022P.R.China Department of Respiratory Medicine Affiliated Jinling HospitalMedical School of Nanjing UniversityNanjingJiangsu 210002P.R.China Department of Respiratory Medicine Affiliated Hospital of Nanjing University of Chinese MedicineJiangsu Province Hospital of Chinese MedicineNanjingJiangsu 210029P.R.China Department of Shanghai Lung Cancer Center Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200030P.R.China Beijing Key Laboratory of Mental Disorders National Clinical Research Center for Mental Disorders&National Center for Mental DisordersBeijing Anding HospitalCapital Medical UniversityBeijing 200030China Advanced Innovation Center for Human Brain Protection Capital Medical UniversityBeijing 200030China Senior Department of Pathology the 7th Medical Center of PLA General HospitalBeijing 100700P.R.China Department of Cancer Molecular Diagnostics Core Tianjin Medical University Cancer Institute and HospitalTianjin 300060P.R.China Guangdong Lung Cancer Institute Guangdong Provincial Laboratory of Translational Medicine in Lung CancerGuangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesSchool of MedicineGuangzhouGuangdong 510080P.R.China State Key Laboratory of Molecular Oncology Department of Medical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021P.R.China Department of Medical Oncology Lung Cancer and Gastrointestinal UnitHunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School

The BRAF gene is an important signaling molecule in human cells that is involved in the regulation of cell growth,differentiation,and *** the BRAF gene mutates,it can lead to abnormal activation of the signaling pathway,which promotes cell proliferation,inhibits cell apoptosis,and ultimately contributes to the occurrence and development of *** mutations are widely present in various cancers,including malignant melanoma,thyroid cancer,colorectal cancer,non-small cell lung cancer,and hairy cell leukemia,among *** is an important target for the treatment of various solid tumors,and targeted combination therapies,represented by BRAF inhibitors,have become one of the main treatment modalities for a variety of BRAF-mutation-positive solid tumors.

关键词： BRAF diagnosis treatment

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New binary artificial bee colony for the 0-1 knapsack problem 9th

New binary artificial bee colony for the 0-1 knapsack proble...

引用

9th International Conference on Swarm Intelligence, ICSI 2018

作者： Nouioua, Mourad Li, Zhiyong Jiang, Shilong The College of Computer Science and Electronic Engineering Hunan University Changsha China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China PKU-HKUST Shenzhen-HongKong Institution Shenzhen China

ISBN: (纸本)9783319938141

The knapsack problem is one of the well known NP-Hard optimization problems. Because of its appearance as a sub-problem in many real world problems, it attracts the attention of many researchers on swarm intelligence and evolutionary computation community. In this paper, a new binary artificial bee colony called NB-ABC is proposed to solve the 0-1 knapsack problem. Instead of the search operators of the original ABC, new binary search operators are designed for the different phases of the ABC algorithm, namely the employed, the onlooker and the scout bee phases. Moreover, a novel hybrid repair operator called (HRO) is proposed to repair and improve the infeasible solutions. To assess the performance of the proposed algorithm, NB-ABC is compared with two other existing algorithms, namely GB-ABC and BABC-DE, for solving the 0-1 knapsack problem. Based on a set of 15 0-1 high dimensional knapsack problems classified in three categories. the experimental results in view of many criteria show the efficiency and the robustness of the proposed NB-ABC. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Repair

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A decomposition based evolutionary algorithm with angle penalty selection strategy for many-objective optimization 9th

A decomposition based evolutionary algorithm with angle pena...

引用

9th International Conference on Swarm Intelligence, ICSI 2018

作者： Li, Zhiyong Lin, Ke Nouioua, Mourad Jiang, Shilong Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha China PKU-HKUST Shenzhen-HongKong Institution Shenzhen China

ISBN: (纸本)9783319938141

Evolutionary algorithms (EAs) based on decomposition have shown to be promising in solving many-objective optimization problems (MaOPs). First, the population (or objective space) is divided into K subpopulations (or subregions) by a group of uniform distribution reference vectors. Later, subpopulations are optimized simultaneously. In this paper, we propose a new decomposition based evolutionary algorithm with angle penalty selection strategy for MaOPs (MOEA-APS). In the environmental selection process, in order to prevent the solutions located around the boundary of the subregion from being simultaneously selected into the next generation which will affect negatively on the performance of the algorithm, a new angle similarity measure (AS) is calculated and used to punish the dense solutions. More precisely, after selecting a good solution x for a sub population, the solutions whose angle similarity with x exceeding η or pareto dominated by x will be directly punished. Moreover, The threshold η is not fixed, but decided by the distribution of the solutions around x. This mechanism allows to improve diversity of population. The experimental results on DTLZ benchmark test problems show that the results of the proposed algorithm are very competitive comparing with four other state-of-the-art EAs for MaOPs. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Evolutionary algorithms

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Distributed resource scheduling for large-scale MEC systems: A multi-agent ensemble deep reinforcement learning with imitation acceleration

arXiv

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arXiv 2020年

作者： Jiang, Feibo Dong, Li Wang, Kezhi Yang, Kun Pan, Cunhua Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Hunan University of Commerce Changsha China Department of Computer and Information Sciences Northumbria University United Kingdom School of Computer Sciences and Electrical Engineering University of Essex ColchesterCO4 3SQ United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom

We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large-scale mobile edge computing (MEC) system. To address this problem, we propose a distributed intelligent resource scheduling (DIRS) framework, which includes centralized training relying on the global information and distributed decision making by each agent deployed in each MEC server. More specifically, we first introduce a novel multi-agent ensemble-assisted distributed deep reinforcement learning (DRL) architecture, which can simplify the overall neural network structure of each agent by partitioning the state space and also improve the performance of a single agent by combining decisions of all the agents. Secondly, we apply action refinement to enhance the exploration ability of the proposed DIRS framework, where the near-optimal state-action pairs are obtained by a novel Lvy flight search. Finally, an imitation acceleration scheme is presented to pre-train all the agents, which can significantly accelerate the learning process of the proposed framework through learning the professional experience from a small amount of demonstration data. Extensive simulations are conducted to demonstrate that the proposed DIRS framework is efficient and outperforms the existing benchmark schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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