We present a theoretical study of quantum charge pumping in metallic armchair graphene nanoribbons using the Floquet Green function method. A central part of the ribbon acting as the scattering region is supposed to h...We present a theoretical study of quantum charge pumping in metallic armchair graphene nanoribbons using the Floquet Green function method. A central part of the ribbon acting as the scattering region is supposed to have staggered sublattiee potential to open a finite band gap. A single ae gate is asymmetrically applied to a part of the scattering region to drive the pumping. Corresponding to the gap edges, there are two pumped current peaks with opposite current directions, which can be reversed by changing the position of the ac gate relative to the scattering region. The effects of the parameters, such as the staggered sublattice potential, the driving frequency and the geometric parameters of the structure, on the pumping are discussed.展开更多
Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a mult...Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.展开更多
To improve the performance of chaotic secure communication,three simplified chaotic systems with one variable parameter were investigated.Basic properties were analyzed including symmetry,dissipation and topological s...To improve the performance of chaotic secure communication,three simplified chaotic systems with one variable parameter were investigated.Basic properties were analyzed including symmetry,dissipation and topological structure.Complex dynamical behaviors of the systems including chaos and periodic orbits were verified by numerical simulations,Lyapunov exponents and bifurcation diagrams.Interestingly,the three systems were integrated in a common circuit,and their dynamical behaviors were easily observed by adjusting regulable resistors R28,R14 and R17,respectively,and the relations between the variable resistor and the system parameter were deduced.The circuit experiment results agree well with the simulation results.Finally,a secure communication scheme based on chaos shift keying(CSK) was presented,which lays an experiment foundation for chaotic digital secure communication.展开更多
The initial condition Ωde（zini）=n^2（1＋zini）^-2/4 at zini = 2000,widely used to solve the differential equation of the density of the new agegraphic dark energy（NADE） Ωde,makes the NADE model a single-paramete...The initial condition Ωde（zini）=n^2（1＋zini）^-2/4 at zini = 2000,widely used to solve the differential equation of the density of the new agegraphic dark energy（NADE） Ωde,makes the NADE model a single-parameter dark-energy cosmological model.However,we find that this initial condition is only applicable in a flat universe with only dark energy and pressureless matter.In fact,in order to obtain more information from current observational data,such as the cosmic microwave background（CMB） and the baryon acoustic oscillations（BAO）,we need to consider the contribution of radiation.For this situation,the initial condition mentioned above becomes invalid.To overcome this shortcoming,we investigate the evolutions of dark energy in matter-dominated and radiation-dominated epochs,and obtain a new initial condition de（zini）=n2（1＋zini）-2（1＋F（zini））2/4 at z ini = 2000,where F（z）≡Ωr0（1＋z）/[Ωm0＋Ωr0（1＋z）] with Ωr0 and Ωm0 being the current density parameters of radiation and pressureless matter,respectively.This revised initial condition is applicable for the differential equation of Ωde obtained in the standard Friedmann-Robertson-Walker（FRW） universe with dark energy,pressureless matter,radiation,and even spatial curvature,and can still keep the NADE model as a single-parameter model.With the revised initial condition and the observational data of type Ia supernova（SNIa）,CMB,and BAO,we finally constrain the NADE model.The results show that the single free parameter n of the NADE model can be constrained tightly.展开更多
基金Supported by the K.C.Wong Magna Fund in Ningbo Universitythe National Natural Science Foundation of China under Grant No 11474174
文摘We present a theoretical study of quantum charge pumping in metallic armchair graphene nanoribbons using the Floquet Green function method. A central part of the ribbon acting as the scattering region is supposed to have staggered sublattiee potential to open a finite band gap. A single ae gate is asymmetrically applied to a part of the scattering region to drive the pumping. Corresponding to the gap edges, there are two pumped current peaks with opposite current directions, which can be reversed by changing the position of the ac gate relative to the scattering region. The effects of the parameters, such as the staggered sublattice potential, the driving frequency and the geometric parameters of the structure, on the pumping are discussed.
基金supported by National Key R&D Program of China(Grant No.2022YFC3003903)the S&T Program of Hebei(Grant No.19275408D),the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B1111200001)+1 种基金the Key Project of Monitoring,Early Warning and Prevention of Major Natural Disasters of China(Grant No.2019YFC1510304)the Joint Fund of Key Laboratory of Atmosphere Sounding,CMA,and the Research Centre on Meteorological Observation Engineering Technology,CMA(Grant No.U2021Z05).
文摘Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.
基金Projects(611061006,61073187) supported by the National Nature Science Foundation of China
文摘To improve the performance of chaotic secure communication,three simplified chaotic systems with one variable parameter were investigated.Basic properties were analyzed including symmetry,dissipation and topological structure.Complex dynamical behaviors of the systems including chaos and periodic orbits were verified by numerical simulations,Lyapunov exponents and bifurcation diagrams.Interestingly,the three systems were integrated in a common circuit,and their dynamical behaviors were easily observed by adjusting regulable resistors R28,R14 and R17,respectively,and the relations between the variable resistor and the system parameter were deduced.The circuit experiment results agree well with the simulation results.Finally,a secure communication scheme based on chaos shift keying(CSK) was presented,which lays an experiment foundation for chaotic digital secure communication.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 10705041,10975032,11047112,and 11175042)the Program for New Century Excellent Talents at the University of Ministry of Education of China (Grant No. NCET-09-0276)the National Ministry of Education of China(Grant Nos. N100505001 and N110405011)
文摘The initial condition Ωde（zini）=n^2（1＋zini）^-2/4 at zini = 2000,widely used to solve the differential equation of the density of the new agegraphic dark energy（NADE） Ωde,makes the NADE model a single-parameter dark-energy cosmological model.However,we find that this initial condition is only applicable in a flat universe with only dark energy and pressureless matter.In fact,in order to obtain more information from current observational data,such as the cosmic microwave background（CMB） and the baryon acoustic oscillations（BAO）,we need to consider the contribution of radiation.For this situation,the initial condition mentioned above becomes invalid.To overcome this shortcoming,we investigate the evolutions of dark energy in matter-dominated and radiation-dominated epochs,and obtain a new initial condition de（zini）=n2（1＋zini）-2（1＋F（zini））2/4 at z ini = 2000,where F（z）≡Ωr0（1＋z）/[Ωm0＋Ωr0（1＋z）] with Ωr0 and Ωm0 being the current density parameters of radiation and pressureless matter,respectively.This revised initial condition is applicable for the differential equation of Ωde obtained in the standard Friedmann-Robertson-Walker（FRW） universe with dark energy,pressureless matter,radiation,and even spatial curvature,and can still keep the NADE model as a single-parameter model.With the revised initial condition and the observational data of type Ia supernova（SNIa）,CMB,and BAO,we finally constrain the NADE model.The results show that the single free parameter n of the NADE model can be constrained tightly.
