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Universality of the dynamic characteristic relationship of electron correlation in the two-photon double ionization process of a helium-like system

arXiv

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arXiv 2020年

作者： Li, Fei Yang, Yu-Jun Chen, Jing Liu, Xiao-Jun Wei, Zhi-Yi Wang, Bing-Bing Laboratory of Optical Physics Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Institute of Atomic and Molecular Physics Jilin University Changchun130012 China Institute of Applied Physics and Computational Mathematics P. O. Box 8009 Beijing100088 China HEDPS Center for Applied Physics and Technology Peking University Beijing100084 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Science Wuhan430071 China University of Chinese Academy of Sciences Beijing100049 China

Universality of the dynamic characteristic relationship between the characteristic time tc and the two-electron Coulomb interaction energy V 12 of the ground state in the two-photon double ionization process is investigated through changing the parameters of the two-electron atomic system and the corresponding laser conditions. The numerical results show that the product tcV 12 keeps constant around 4.1 in the cases of changing the nucleus charge, the electron charge, the electron mass, and changing simultaneously the nucleus charge and the electron charge. These results demonstrate that the dynamic characteristic relationship in the two-photon double ionization process is universal. This work sheds more light on the the dynamic characteristic relationship in ultrafast processes and may find its application in the measurement of attosecond pulses. Copyright © 2020, The Authors. All rights reserved.

关键词： Helium

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Station Layout Optimization Genetic Algorithm for Four Stations TDOA Location

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Journal of physics: Conference Series 2019年第6期1176卷

作者： Ruiqi Sun Zhonghang He Lu Gao Jinliang Bai National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing 100076

Station layout has a direct impact on localization precision for four-station TDOA (time difference of arrival) location system. In order to optimize the overall location precision of targets in certain area, genetic algorithm for station layout optimization is presented. GDOP is regarded as the measurement rule of location precision. Then the multi-object programming mathematical model of station layout optimization is built. The optimal solution is searched by genetic algorithm. Consequently, the optimal layout of station is obtained. The simulation provides the GDOP distribution of two station layouts. One is the initial station layout, and the other is the optimal station layout. The simulation results show that for the optimal station layout, the effect of improving the location precision is obvious, and also indicate the validity of genetic algorithm.

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Dominant SST Mode in the Southern Hemisphere Extratropics and Its Influence on Atmospheric Circulation

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Advances in Atmospheric sciences 2018年第7期35卷 881-895页

作者： Fei ZHENG Jianping LI Fred KUCHARSKI Ruiqiang DING Ting LIU State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences State Key Laboratory of Earth Surface Processes and Resource Ecology and College of Global Change and Earth System Science Beijing Normal University Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology Earth System Physics Section Abdus Salam International Centre for Theoretical Physics Center of Excellence for Climate Change Research Department of MeteorologyKing Abdulaziz University Plateau Atmosphere and Environment Key Laboratory of Sichuan Province Chengdu University of Information Technology State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography

The variability in the Southern Ocean（SO） sea surface temperature（SST） has drawn increased attention due to its unique physical features; therefore, the temporal characteristics of the SO SST anomalies（SSTA） and their influence on extratropical atmospheric circulation are addressed in this study. Results from empirical orthogonal function analysis show that the principal mode of the SO SSTA exhibits a dipole-like structure, suggesting a negative correlation between the SSTA in the middle and high latitudes, which is referred to as the SO Dipole（SOD） in this study. The SOD features strong zonal symmetry, and could reflect more than 50% of total zonal-mean SSTA variability. We find that stronger（weaker） Subantarctic and Antarctic polar fronts are related to the positive（negative） phases of the SOD index, as well as the primary variability of the large-scale SO SSTA meridional gradient. During December–January–February, the Ferrel cell and the polar jet shift toward the Antarctic due to changes in the SSTA that could be associated with a positive phase of the SOD, and are also accompanied by a poleward shift of the subtropical jet. During June–July–August, in association with a positive SOD, the Ferrel cell and the polar jet are strengthened, accompanied by a strengthened subtropical jet. These seasonal differences are linked to the differences in the configuration of the polar jet and the subtropical jet in the Southern Hemisphere.

关键词： extratropical sea surface temperature air–sea interaction Southern Annular Mode

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Spin-Triplet Excitonic Insulator: The Case of Semihydrogenated Graphene

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Physical Review Letters 2020年第16期124卷 166401-166401页

作者： Zeyu Jiang Wenkai Lou Yu Liu Yuanchang Li Haifeng Song Kai Chang Wenhui Duan Shengbai Zhang State Key Laboratory of Low-Dimensional Quantum Physics and Collaborative Innovation Center of Quantum Matter Department of Physics Tsinghua University Beijing 100084 China SKLSM Institute of Semiconductors Chinese Academy of Sciences P.O. Box 912 Beijing 100083 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 China Key Lab of advanced optoelectronic quantum architecture and measurement (MOE) and Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing 100081 China CAEP Software Center for High Performance Numerical Simulation Beijing 100088 China Beijing Academy of Quantum Information Sciences Beijing 100193 China Institute for Advanced Study Tsinghua University Beijing 100084 China Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute Troy New York 12180 USA

While various excitonic insulators have been studied in the literature, due to the perceived too-small spin splitting, spin-triplet excitonic insulator is rare. In two-dimensional systems such as a semihydrogenated graphene (known as graphone), however, it is possible, as revealed by first-principles calculations coupled with Bethe-Salpeter equation. The critical temperature, given by an effective Hamiltonian, is 11.5 K. While detecting excitonic insulators is still a daunting challenge, the condensation of triplet excitons will result in spin superfluidity, which can be directly measured by a transport experiment. Nonlocal dielectric screening also leads to an unexpected phenomenon, namely, an indirect-to-direct transition crossover between single-particle band and exciton dispersion in the semihydrogenated graphene, which offers yet another test by experiment.

关键词： Excitons Graphene First-principles calculations

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Correction to: Intensification and Northward extension of Northwest Pacific anomalous anticyclone in El Niño decaying mid-summer: an energetic perspective

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Climate Dynamics 2021年第1期58卷 607-607页

作者： Tang, Haosu Hu, Kaiming Huang, Gang Wang, Ya Tao, Weichen State key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics and Center for Monsoon System Research Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology Qingdao China IAP/CAS Beijing China

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A novel non-enzymatic hydrogen peroxide sensor based on Co:ZnO modified electrodes

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Progress in Natural science:Materials International 2018年第1期28卷 24-27页

作者： Long Wang Tong Wu Han Wu Jun Zhong Ning Wang Rongming Wang Department of Equipment Manufacture Zhongshan Torch Polytechnic National Institute of Metrology China National Computer Products Quality Supervising Test Center Beijing Key Laboratory for Carbon-Based Functional Materials and Devices Institute of Functional Nano and Soft Materials Laboratory (FUNSOM) Soochow University Center for Green Innovation School of Mathematics and Physics University of Science and Technology Beijing

There is currently intense interest in the use of nanoparticles for a wide range of biomedical and technological applications. In this paper, the hierarchical Co doped ZnO nanoflowers were synthesized by a facile wet chemical method and explored as biosensing material. The as-modified novel hydrogen peroxide sensor exhibited a wide linear range（0.25–20 mM）, highly reproducible response（R.S.D. of 2.7%） and long-term stability. The doping Co2+ions carried out the oxidations rapidly and efficiently for the catalysis of hydrogen peroxide（H2O2）. A high activity toward H2O2in the presence of ascorbic acid（AA） and NaNO2, which are only common for natural enzymes, has also been demonstrated. The good analytical performance, low cost and straightforward preparation method makes this doped semiconductor promising for a wide range of potential applications in medicine, biotechnology and environmental chemistry.

关键词： Nonenzymatic H2O2 sensor Co:ZnO Nanoflowers Electrocatalysis

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Improving the simulation of terrestrial water storage anomalies over China using a Bayesian model averaging ensemble approach

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Atmospheric and Oceanic science Letters 2018年第4期11卷 322-329页

作者： LIU Jian-Guo JIA Bing-Hao XIE Zheng-Hui SHI Chun-Xiang School of Mathematics and Computational Science and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric Physics Chinese Academy of Sciences National Meteorological Information Center China Meteorological Administration

The ability to estimate terrestrial water storage(TWS)is essential for monitoring hydrological extremes(e.g.,droughts and floods)and predicting future changes in the hydrological ***,inadequacies in model physics and parameters,as well as uncertainties in meteorological forcing data,commonly limit the ability of land surface models(LSMs)to accurately simulate *** this study,the authors show how simulations of TWS anomalies(TWSAs)from multiple meteorological forcings and multiple LSMs can be combined in a Bayesian model averaging(BMA)ensemble approach to improve monitoring and *** using three forcing datasets and two LSMs were conducted over China's Mainland for the period 1979–*** the simulations showed good temporal correlations with satellite observations from the Gravity Recovery and Climate Experiment during 2004–*** correlation coefficient ranged between 0.5 and 0.8 in the humid regions(e.g.,the Yangtze river basin,Huaihe basin,and Zhujiang basin),but was much lower in the arid regions(e.g.,the Heihe basin and Tarim river basin).The BMA ensemble approach performed better than all individual member *** captured the spatial distribution and temporal variations of TWSAs over China's Mainland and the eight major river basins very well;plus,it showed the highest R value(>0.5)over most basins and the lowest root-mean-square error value(<40 mm)in all basins of *** good performance of the BMA ensemble approach shows that it is a promising way to reproduce long-term,high-resolution spatial and temporal TWSA data.

关键词： Terrestrial water storage anomalies multi-forcing and multi-model ensemble simulation Bayesian model averaging spatiotemporal variation uncertainty

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Study of RF structure and Beam Wave Interaction system for a W-band Sheet Beam EIK

Study of RF structure and Beam Wave Interaction system for a...

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2017 International Conference on Radar Systems, Radar 2017

作者： Chen, Shuyuan Liu, Jiaqi Gao, Lu Bai, Jinliang Jiang, Zhiye Xu, Feng Qin, Peng Liu, Hongyan Liu, Xin Li, Hu Gao, Jingpeng National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing100076 China

ISBN: (纸本)9781785615153

Sheet beam Extended Interaction Klystron (EIK) is an attractive Millimeter Waves (MMW) amplifier because of its high gain per unit length and compact configuration, which can be used in radar transmission system. In this paper, RF structure and beam wave interaction system of W band sheet beam EIK has been designed. A new and effective method of designing and studying the beam wave interaction system is presented in this *** whole tube consists of one single-gap cavity, six tri-gaps cavities and one five-gaps cavity. By optimizing the position of cavities, the output power can achieve 30 kW and high gain of 50 dB, which is calculated by three dimensional particle in cell (3D-PIC)*** provides a powerful basis for the subsequent study of sheet beam EIK. © 2017 Institution of Engineering and technology. All rights reserved.

关键词： Millimeter waves

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Deep learning to evaluate seismic-induced soil liquefaction and modified transfer learning between various data sources

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Underground Space 2025年

作者： Hongwei Guo Chao Zhang Hongyuan Fang Timon Rabczuk Xiaoying Zhuang Department of Geotechnical Engineering College of Civil Engineering Tongji University Shanghai 200092 China Key Laboratory of Urban Security and Disaster Engineering Ministry of Education Beijing University of Technology Beijing 100124 China School of Water Conservancy and Transportation/Yellow River Laboratory/Underground Engineering Research Institute Zhengzhou University Zhengzhou 450001 China National Local Joint Engineering Laboratory of Major Infrastructure Testing and Rehabilitation Technology Zhengzhou 450001 China Collaborative Innovation Center for Disaster Prevention and Control of Underground Engineering Jointly Built by Provinces and Ministries Zhengzhou 450001 China Institute of Structural Mechanics Bauhaus University Weimar Weimar 99425 Germany Chair of Computational Science and Simulation Technology Faculty of Mathematics and Physics Leibniz University Hannover Hannover 30167 Germany

Soil liquefaction assessment remains a crucial and complex challenge in seismic geotechnical engineering due to various liquefaction records and limited information, which entails a more generalized off-the-shelf model that can achieve favourable performance on different data sources. In this work, a deep learning model is built and investigated on the soil liquefaction prediction and a modified transfer learning scheme between different data sources is presented. Various datasets, including shear wave velocity-based, CPT-based, SPT-based, and real cases, are collected and utilized to verify the effectiveness and accuracy of the proposed model. Because different data sources in soil liquefaction generally share several geotechnical and mechanical parameters, we work to combine model prior information, feature mapping and data reconstruction in transfer learning models to tackle multi-source domain adaption, which can be further applied to other predictive analysis and facilitate online learning models in geotechnical engineering. Also, the deep learning model is compared with several classical machine learning and ensemble learning models and the modified transfer learning model is formulated by comparing different feature transformation techniques integrated with various feature-based and instance-based transfer learning methods. The accuracy and effectiveness of the deep learning and modified transfer learning models have been validated in the numerical study.

关键词： Liquefaction Prediction Deep learning Ensemble methods Transfer learning Feature-based Instance-based Source data Target data Deep autoencoder Variational autoencoder

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Progress in ENSO prediction and predictability study

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national science Review 2018年第6期5卷 826-839页

作者： Youmin Tang Rong-Hua Zhang Ting Liu Wansuo Duan Dejian Yang Fei Zheng Hongli Ren Tao Lian Chuan Gao Dake Chen Mu Mu State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Environmental Science and Engineering University of Northern British Columbia Prince George Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences Qingdao National Laboratory for Marine Science and Technology State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of Sciences College of Oceanography Hohai University International Center for Climate and Environment Science Institute of Atmospheric PhysicsChinese Academy of Sciences Laboratory for Climate Studies & CMA—NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological Administration College of Atmospheric and Oceanic Science Fudan University

ENSO is the strongest interannual signal in the global climate system with worldwide climatic, ecological and societal impacts. Over the past decades, the research about ENSO prediction and predictability has attracted broad attention. With the development of coupled models, the improvement in initialization schemes and the progress in theoretical studies, ENSO has become the most predictable climate mode at the time scales from months to seasons. This paper reviews in detail the progress in ENSO predictions and predictability studies achieved in recent years. An emphasis is placed on two fundamental issues: the improvement in practical prediction skills and progress in the theoretical study of the intrinsic predictability limit. The former includes progress in the couple models, data assimilations, ensemble predictions and so on, and the latter focuses on efforts in the study of the optimal error growth and in the estimate of the intrinsic predictability limit.

关键词： ENSO prediction and predictability coupled model ensemble prediction optimal error growth probabilistic prediction

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