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Quasiparticle and transport properties of disordered bilayer graphene

Physical Review B 2023年第6期108卷 064208-064208页

作者： Yanru Chen Bo Fu Jinrong Xu Qinwei Shi Ping Cui Zhenyu Zhang International Center for Quantum Design of Functional Materials (ICQD) Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui 230026 China Hefei National Laboratory University of Science and Technology of China Hefei Anhui 230088 China Department of Physics The University of Hong Kong Pokfulam Road Hong Kong China School of Sciences Great Bay University Dongguan 523000 China Key Laboratory of Advanced Electronic Materials and Devices School of Mathematics and Physics Anhui Jianzhu University Hefei Anhui 230601 China

In recent experimental and theoretical studies of graphene, disorder scattering processes have been suggested to play an important role in its electronic and transport properties. In a preceding paper, it has been shown that the nonperturbative momentum-space Lanczos method is able to accurately describe all the multiple impurity scattering events and account for the quasiparticle and transport properties of disordered monolayer graphene. In the present study, we expand the range of applicability of this recursive method by numerically investigating the quasiparticle and transport properties of Bernal-stacked bilayer graphene in the presence of scalar Anderson disorder. The results are further compared with the findings of the same system using a self-consistent Born approximation, as well as the central findings in the preceding paper for monolayer graphene. It is found that in both systems, proper inclusions of all the scattering events are needed in order to reliably capture the role of disorder via multiple impurity scattering. Furthermore, we reveal the dependences of the transport properties of disordered bilayer graphene on the carrier density and temperature, and explore the role of interlayer scattering at varying strengths. Our findings may help to provide some new angles into the quasiparticle and transport properties of disordered bilayer graphene.

关键词： Dirac fermions Quantum transport Quasiparticles & collective excitations Bilayer graphene Disordered systems

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Mixture of Experts for Network Optimization: A Large Language Model-enabled Approach

arXiv

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arXiv 2024年

作者： Du, Hongyang Liu, Guangyuan Lin, Yijing Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Optimizing various wireless user tasks poses a significant challenge for networking systems because of the expanding range of user requirements. Despite advancements in Deep Reinforcement Learning (DRL), the need for customized optimization tasks for individual users complicates developing and applying numerous DRL models, leading to substantial computation resource and energy consumption and can lead to inconsistent outcomes. To address this issue, we propose a novel approach utilizing a Mixture of Experts (MoE) framework, augmented with Large Language Models (LLMs), to analyze user objectives and constraints effectively, select specialized DRL experts, and weigh each decision from the participating experts. Specifically, we develop a gate network to oversee the expert models, allowing a collective of experts to tackle a wide array of new tasks. Furthermore, we innovatively substitute the traditional gate network with an LLM, leveraging its advanced reasoning capabilities to manage expert model selection for joint decisions. Our proposed method reduces the need to train new DRL models for each unique optimization problem, decreasing energy consumption and AI model implementation costs. The LLM-enabled MoE approach is validated through a general maze navigation task and a specific network service provider utility maximization task, demonstrating its effectiveness and practical applicability in optimizing complex networking systems. © 2024, CC BY.

关键词： Reinforcement learning

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Correction to:Study on the resource utilization of high fluorine-containing organic waste through fluidized incineration

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Waste Disposal and Sustainable Energy 2023年第2期5卷 245-245页

作者： Wenhan Li Zengyi Ma Jianhua Yan Qianming Huang Xingjian Wen Zian Zhai Bochen Huang Shuang Wang Yongqiang Chen Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu610213China State Key Laboratory of Clean Energy Utilization Institute for Thermal Power EngineeringZhejiang UniversityHangzhou310027China Zhejiang Xianchuang Energy&Technology Co.Ltd Jinhua321000China

Correction to:Waste Disposal&Sustainable Energy(2022)4:117-129 https://***/10.1007/s42768-022-00101-7 The section Confict of interest'has been amended:'Jian-hua Yan is the Editor in-Chief of Waste Disposal&Sustain-able Energy.'The revised'Confict of interest'is as follows:Jianhua Yan is the Editor-in-Chief of Waste Disposal&Sustainable *** behalf of all authors,the corresponding author states that there is no conflict of interest.

关键词： Sustainable fluorine behalf

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Neutronic and thermal-mechanical coupling schemes for heat pipe cooled reactor designs

Neutronic and thermal-mechanical coupling schemes for heat p...

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2020 International Conference on Nuclear Engineering, ICONE 2020, collocated with the ASME 2020 Power Conference

作者： Ma, Yugao Liu, Minyun Han, Wenbin Xie, Biheng Chai, Xiaoming Huang, Shanfang Yu, Hongxing Department of Engineering Physics Tsinghua University Beijing China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China

ISBN: (纸本)9780791883785

Space fission power systems can enable ambitious solarsystem and deep-space science missions. The heat pipe cooled reactor is one of the most potential candidates for near-term space power supply, featured with safety, simplicity, reliability, and modularity. Heat pipe cooled reactors are solid-state and high temperature (up to 1500 K) reactors, where the thermal expansion is remarkable and the mechanical response significantly influences the neutronics and thermal analyses. Due to the considerable difference between heat pipe cooled reactors and traditional water reactors in the structure and design concept, the coupling solutions for light water reactors cannot be directly applied to heat pipe cooled reactor analyses. Therefore, new coupling framework and program need to consider the coupling effects among neutronics, heat transfer as well as mechanics. Based on the Monte Carlo program RMC and commercial finite element program ANSYS Mechanical APDL, this work introduces the three coupling fields of neutronics (N), thermal (T), and mechanics (M) for heat pipe cooled reactors. The neutronic and thermal-mechanical (N/T-M) coupling strategy is developed theoretically, focusing on the formulation of the nonlinear problem, iteration schemes, and relaxation methods. Besides, the finite element method and the Monte Carlo program use different meshes and geometry construction methods. The spatial mapping and geometry reconstruction are also essential for the N/T-M coupling, which is discussed and established in detail. Furthermore, the N/T-M coupling methods are applied to the preliminary self-designed 10 kWe space heat pipe cooled reactor. Coupling shows that the thermal-mechanical feedback in the solid-state reactor has negative reactivity feedback (-2007 pcm) while it has a deterioration in heat transfer due to the expansion in the gas gap. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Heat pipes

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Anomaly Detection-Oriented High-Frequency Signal Storage for Diesel Engines 4

Anomaly Detection-Oriented High-Frequency Signal Storage for...

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4th IEEE International Conference on Computer and Communication Engineering technology, CCET 2021

作者： Huang, He Xu, Bailing Luo, Hao Zhuang, Haoran Liu, Xuewei Ma, Liyong Naval University of Engineering National Key Laboratory for Vessel Integrated Power System Technology Wuhan China Shanghai Marine Diesel Engine Research Institute Shanghai China School of Information Science and Engineering Harbin Institute of Technology Weihai China

ISBN: (纸本)9781665438902

Marine diesel engine has been the main power of civil ships, small and medium-sized ships and conventional submarines. Anomaly detection on diesel engines is very important for the safety of marine systems. Diesel engine anomaly detection requires access to a large number of high-frequency signals. How to store these signals to support anomaly detection applications is currently rarely studied. This article discusses the design of high-frequency signal storage systems that provide data support for intelligent anomaly detection systems. It mainly focuses the design of database system and file system for high-frequency signal storage requirements of diesel engines. The actual operation shows that the system designed in this paper can support the storage of high-frequency signals and the deployment of anomaly detection applications. © 2021 IEEE.

关键词： Diesel engines

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Research on Open-Set Recognition Methods for Rolling Bearing Fault Diagnosis

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Sensors (Basel, Switzerland) 2025年第10期25卷 3019页

作者： Jia Xu Yan Wang Renyi Xu Hailin Wang Xinzhi Zhou School of Electronic Information Sichuan University Chengdu 610065 China. National Key Laboratory of Science and Technology on Reactor System Design Technology Nuclear Power Institute of China Chengdu 610213 China.

In rolling bearing fault diagnosis, when an unknown fault is present, the Closed-Set Recognition (CSR) method tends to misclassify it as a known fault. To address this issue, an Open-Set Recognition (OSR) framework is proposed for rolling bearing fault diagnosis in this study. The framework is built upon a serial multi-scale convolutional prototype learning (SMCPL) network, enhanced with an efficient channel attention (ECA) mechanism to extract the most critical fault features. The extracted features are fed into the Density Peak Clustering (DPC) module, which identifies known and unknown classes based on the computed local densities and relative distances. Finally, validation is performed on the Case Western Reserve University (CWRU) dataset, the Xi'an Jiaotong University rolling bearing accelerated life test dataset (XJTU-SY), and the Paderborn University bearing dataset (PU), Germany, and the framework is comprehensively evaluated in terms of several evaluation metrics, such as normalization accuracy and feature visualization. The experimental results show that SMCPL-ECA-DPC outperforms the comparative methods of SMCPL, CPL, ANEDL, CNN, and OpenMax and has high diagnostic performance in the identification of unknown faults.

关键词： Open-Set Recognition multi-scale rolling bearings unknown fault diagnosis

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Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

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Advances in Atmospheric sciences 2024年第7期41卷 1299-1312页

作者： Ya WANG Gang HUANG Baoxiang PAN Pengfei LIN Niklas BOERS Weichen TAO Yutong CHEN BO LIU Haijie LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Earth System Modelling School of Engineering and DesignTechnical University of MunichOttobrunn 85521Germany Potsdam Institute for Climate Impact Research Potsdam 14412Germany Department of Mathematics and Global Systems Institute University of ExeterExeter EX44QEUK CMA Earth System Modeling and Prediction Centre(CEMC) Chinese Academy of Meteorological SciencesBeijing 100081China

Climate models are vital for understanding and projecting global climate change and its associated ***,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future *** these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning ***,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth system Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST ***,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to ***,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to *** enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales *** study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

关键词： generative adversarial networks model bias deep learning El Niño-Southern Oscillation marine heatwaves

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SGNet: A Multi-Scale Method for Steel Surface Defect Detection

SGNet: A Multi-Scale Method for Steel Surface Defect Detecti...

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Smart World Congress (SWC), IEEE

作者： Shanshan Liu Xiangzhi Liu Jiazheng Man Bingyang Cao Yunfeng Dong Xiaoming Wu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

The large variation in target scales within steel surface defect images often results in low detection accuracy. To address this issue, we have developed a multi-scale defect detection method named SGNet. Initially, we introduced a Self-Guided Bi-Level Routing Transformer (SG-BiFormer) as the backbone network of our model. SG-BiFormer utilizes a self-guided strategy to model global information and dynamically reallocates tokens based on the importance of image regions, increasing token quantity in significant areas to preserve fine-grained details and reducing it in less critical areas. This strategy significantly enhances the accuracy and efficiency of the model in handling multi-scale targets. Subsequently, we incorporated Grouped Separable Convolutions (GSConv) to manage local information of multi-scale features. GSConv automatically adjusts the size and shape of the convolution kernels according to different input features. This design not only improves global information processing capabilities but also ensures sensitive and precise detail capture. Lastly, we employed MPDIoU as the loss function for our model, which optimizes corner positioning to tackle the challenges of regression tasks, substantially improving the accuracy of the model in handling complex defects. Experimental evidence confirms the effectiveness of this method. Our SGNet achieved a 77.1% mAP on the NEU-DET dataset, demonstrating outstanding performance.

关键词： Visualization Accuracy Shape Detectors Transformers Routing Feature extraction Steel Kernel Defect detection

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design of Cooled Dual-Group Linked Continuous Zoom Hybrid Refractive-Diffractive system Based on Double-Layer Diffractive Element

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Guangxue Xuebao/Acta Optica Sinica 2025年第9期45卷

作者： Ma, Chengshuang Li, Ying Xue, Changxi Key Laboratory of Advanced Optical System Design and Manufacturing Technology of Jilin Province Changchun University of Science and Technology Jilin Changchun130022 China Department of Instrument Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China School of Optoelectronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China

Objective In recent years, with increasing demands for imaging optical systems and continuous advancements in manufacturing technologies, dual-band infrared zoom optical systems have been widely applied in various fields such as military reconnaissance, precision guidance, airborne electro-optical pods, aerospace, security, and night vision surveillance. Continuous zoom infrared lenses enable target searching over a wide field of view and rapid switching to a narrow field of view for precise tracking and observation. This capability is particularly advantageous for tracking high-speed moving targets, addressing the issue of losing targets during field-of-view switching in stepped zoom lenses. However, dual-band infrared zoom systems face challenges such as complex structures, difficult aberration correction, suboptimal image quality, and limited material selection. Therefore, developing a high-performance dual-band infrared zoom optical system is crucial for advancing imaging optical systems. Methods First, in the dual-band infrared range of 3.7‒4.8 μm and 8‒10 μm, a double-layer diffractive optical element (DOE) is designed using a method that maximizes polychromatic integrated diffraction efficiency (PIDE) considering angular-wavelength characteristics. The wavelengths corresponding to the maximum PIDE values are selected as the design wavelengths, and the corresponding microstructure height parameters are calculated. The designed double-layer DOE achieves a comprehensive PIDE of 98.29%, demonstrating high diffraction efficiency across the dual-band infrared range. Second, a dual-group linked zoom model is derived. Using this model, the component distances at different focal lengths are calculated. These parameters are then input into optical design software to develop a dual-band infrared zoom optical system with a continuous zoom range of 30‒300 mm. However, the initial system exhibits suboptimal image quality. Finally, the high-efficiency double-layer DOE is in

关键词： Thermography (imaging)

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design of LCoS-Based Twin 1×40 Wavelength Selective Switch

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中兴通讯技术（英文版） 2024年第4期22卷 18-28页

作者： WANG Han LIU Maoqi FENG Zhenhua LIU Minghuan MAO Baiwei School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China WDM System Department of Wireline Product R&D Institute ZTE CorporationWuhan 430223China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China

Wavelength selective switch (WSS) is the crucial component in the reconfigurable optical add/drop multiplexer (ROADM),which plays a pivotal role in the next-generation all-optical networks. We present a compact architecture of twin 1×40 liquid crystal on silicon (LCoS)-based WSS,which can be regarded as a 4f system in the wavelength direction and a 2f system in the switching direction. It is designed with theoretical analysis and simulation investigation. Polarization multiplexing is employed for two sources of twin WSS by polarization con-version before the common optical path. The WSS system attains a coupling efficacy exceeding 96％ for 90％ of the ports through simulation optimization. The 3 dB bandwidth can be achieved by more than 44 GHz at a 50 GHz grid for all 120 channels at all deflection ports. This work establishes a solid foundation for developing high-performance WSS with larger port counts.

关键词： wavelength selective switch (WSS) liquid crystal on silicon (LCoS) optical structure design insertion loss

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