Numerical simulation for the initial state of avalanche in polydisperse particle systems

Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,respectively.In these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse system.By examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse systems.We also consider the distribution characteristics of the average coordination number and average velocity for the moving particles.The results support that the polydisperse particle systems are more stable in the T2 stage.

Effects of initial states on the quantum correlations in the generalized Grover search algorithm

We investigate the correlations between two qubits in the Grover search algorithm with arbitrary initial states by numerical simulation.Using a set of suitable bases,we construct the reduced density matrix and give the numerical expression of correlations relating to the iterations.For different initial states,we obtain the concurrence and quantum discord compared with the success probability in the algorithm.The results show that the initial states affect the correlations and the limit point of the correlations in the searching process.However,the initial states do not influence the whole cyclical trend.

Initial-state dependence of phase behaviors in a dense active system

There are rich emergent phase behaviors in non-equilibrium active systems.Flocking and clustering are two representative dynamic phases.The relationship between both the phases is still unclear.Herein,we numerically investigate the evolution of flocking and clustering in a system consisting of self-propelled particles with active reorientation.We consider the interplay between flocking and clustering phases with different initial configurations,and observe a domain in steady state order parameter phase diagrams sensitive to the choice of initial configurations.Specifically,by tuning the initial degree of polar ordering,either a more ordered flocking or a disordered clustering state can be observed in the steady state.These results enlighten us to manipulate emergent behaviors and collective motions of an active system,and are qualitatively different from the emergence of a new bi-stable regime observed in aligned active particles due to an explicit attraction[New J.Phys.14073033(2012)].

Quantum dynamical speedup for correlated initial states

The maximal evolution speed of any quantum system can be expressed by the quantum speed limit time.In this paper,we consider a model in which the system has a correlation with the environment.The influence of the initial correlation between the system and environment on the quantum speed limit is investigated.It is shown that the appearance of non-Markovianity effects causes the speedup of quantum evolution.Moreover,we demonstrate the dependence of quantum dynamical speedup on the quantum coherence of the correlated initial state.

Finite horizon optimal control of discrete-time nonlinear systems with unfixed initial state using adaptive dynamic programming

In this paper,we aim to solve the finite horizon optimal control problem for a class of discrete-time nonlinear systems with unfixed initial state using adaptive dynamic programming(ADP) approach.A new-optimal control algorithm based on the iterative ADP approach is proposed which makes the performance index function converge iteratively to the greatest lower bound of all performance indices within an error according to within finite time.The optimal number of control steps can also be obtained by the proposed-optimal control algorithm for the situation where the initial state of the system is unfixed.Neural networks are used to approximate the performance index function and compute the optimal control policy,respectively,for facilitating the implementation of the-optimal control algorithm.Finally,a simulation example is given to show the results of the proposed method.

BABAR measurement of baryon time-like form factors via initial state radiation

BABAR has measured with unprecedented accuracy the e^＋e^- → pp and e^＋e^- →∧∧ cross sections by means of the initial state radiation technique, which has the advantages of good efficiency, good energy resolution and full angular acceptance, even exactly at threshold. A peculiar feature of these cross sections is their non-vanishing values at threshold. In the case of charged baryons, this phenomenon is expected according to the Coulomb interaction between the outgoing baryon and antibaryon. Once this Coulomb enhancement factor is taken into account, the striking result is achieved that the proton form factor at threshold is ｜GP（4Mp^2）｜ = 1, that is what is expected for pointlike fermion pairs, in spite of the proton structure. However a Coulomb enhancement factor is not expected for neutral fermions, likely in contradiction with the BABAR data. Qualitatively this behaviour is consistent with Coulomb interactions at the valence quark level.

Roles of initial ocean states on predicting the 2002/03 central Pacific El Nino

The 2002/03 El Ni？o event, a new type of El Ni？o with maximum warm anomaly occurring in the central equatorial Pacific, is known as central-Pacific（CP） El Ni？o. In this study, on the basis of an El Ni？o prediction system, roles of the initial ocean surface and subsurface states on predicting the 2002/03 CP El Ni？o event are investigated to determine conditions favorable for predicting El Ni？o growth and are isolated in three sets of hindcast experiments. The hindcast is initialized through assimilation of only the sea surface temperature（SST）observations to optimize the initial surface condition（Assim_SST）, only the sea level（SL） data to update the initial subsurface state（Assim_SL）, or both the SST and SL data（Assim_SST＋SL）. Results highlight that the hindcasts with three different initial states all can successfully predict the 2002/03 El Ni？o event one year in advance and that the Assim_SST＋SL hindcast performs best. A comparison between the various sets of hindcast results further demonstrates that successful prediction is significantly affected by both of the initial surface and subsurface conditions, but in different developing phases of the 2002/03 El Ni？o event. The accurate initial surface state can easier trigger the prediction of the 2002/03 El Ni？o, whereas a more reasonable initial subsurface state can contribute to improving the prediction in the growth of the warm event.

Thermal deformation behavior and microstructure evolution of modified IN617 alloy with different initial states

The thermal deformation behaviors of the as-cast and wrought modified IN617 nickel-based heat-resistant alloys at different temperatures(1000–1180℃)and strain rates(0.01–1 s^(−1))were studied.The constitutive equation was established to describe the relationship of the flow stress,temperature,and strain rate during thermal deformation.The effect of the thermal deformation conditions on the microstructure evolution of alloys was studied using electron backscatter diffraction.The results revealed that the thermal deformation activation energy of the as-cast alloy was greater than that of the wrought alloy.The dynamic recrystallization(DRX)process is slow at intermediate strain rate(0.1 s^(−1))due to the comprehensive influence of various factors,such as the critical strain of DRX nucleation and stored energy.The DRX volume fraction increases with the improvement of deformation temperature.The varied dynamic softening mechanisms induce the different thermal deformation behaviors of as-cast and wrought alloys.The dynamic recovery,discontinuous dynamic recrystallization(DDRX)and nucleation at slip zone caused by strain incompatibility in grains were observed during thermal deformation of as-cast alloys.In the process of thermal deformation of wrought alloys,DDRX was the primary dynamic crystallization mechanism.The continuous dynamic recrystallization was an auxiliary nucleation mechanism.

Effects of initial electronic state on vortex patterns in counter-rotating circularly polarized attosecond pulses

We theoretically investigate the effects of different electronic states as the initial state on the vortex patterns in photoelectron momentum distributions(PMDs)from numerical solutions of the two-dimensional(2D)time-dependent Schrodinger equation(TDSE)of He^(+)with a pair of counter-rotating circularly polarized attosecond pulses.It is found that the number of spiral arms in vortex patterns is equal to the number of the absorbed photons when the initial state is the ground state.However,the number of spiral arms in vortex patterns is always two more than the number of the absorbed photons when the initial state is the excited state.This sensitivity is attributed to the initial electron density distribution.In addition,we have demonstrated the PMDs for different initial electronic states with the same wavelengths and analyzed their corresponding physical mechanisms.It is illustrated that the method presented can be employed to effectively control the distribution of the electron vortices.

Initial Stable State of Ocean Floor Deposits

Extensive oedometer tests and physical tests have been conducted on remolded and reconstituted marine soils with different initial water contents and liquid limits. The oedometer test data can be well fitted with a straight line in the bilogarithmic ln(1+ e ) ～ lg p plot. The initial effective stress corresponding to the initial void ratio is determined by extrapolation of the bilogarithmic compression line. This new way of extrapolating oedometer test data to the initial void ratio overcomes the difficulty of measuring the residual effective stress of soils in the remolded state. The initial stable compression line of ocean floor deposits under different deposition environments corresponds to the compression line at the sensitivity equal to one. This initial stable compression line obtained in this study is consistent with the available compression line at the sensitivity equal to one which is proposed based on the experimental data of remolded undrained strength and the theoretical concept of Cam clay critical state line.

The Dependence of Chimera States on Initial Conditions

A chimera state consisting of both coherent and incoherent groups is a fascinating spatial pattern in non-locally coupled identical oscillators. It is thought that random initial conditions hardly evolve to chimera states. In this work, we study the dependence of chimera states on initial conditions. We show that random initial conditions may lead to chimera states and the chance of realizing chimera states becomes increasing when the model parameters axe moving away from the boundary of their stable regime.

Dynamic stabilization of atomic ionization in a high-frequency laser field with different initial angular momenta

We investigated the ionization of an atom with different orbital angular momenta in a high-frequency laser field by solving the time-dependent Schr¨odinger equation.The results showed that the ionization stabilization features changed with the relative direction between the angular momentum of the initial state and the vector field of the laser pulse.The ionization mechanism of the atom irradiated by a high frequency was explained by calculating the transition matrix and evolution of the time-dependent wave packet.This study can provide comprehensive understanding to improve atomic nonadiabatic ionization.

High-energy nuclear physics meets machine learning

Although seemingly disparate,high-energy nuclear physics(HENP)and machine learning(ML)have begun to merge in the last few years,yielding interesting results.It is worthy to raise the profile of utilizing this novel mindset from ML in HENP,to help interested readers see the breadth of activities around this intersection.The aim of this mini-review is to inform the community of the current status and present an overview of the application of ML to HENP.From different aspects and using examples,we examine how scientific questions involving HENP can be answered using ML.

A new classification of seepage control mechanisms in geotechnical engineering

Seepage flow through soils,rocks and geotechnical structures has a great influence on their stabilities and performances,and seepage control is a critical technological issue in engineering practices.The physical mechanisms associated with various engineering measures for seepage control are investigated from a new perspective within the framework of continuum mechanics;and an equation-based classification of seepage control mechanisms is proposed according to their roles in the mathematical models for seepage flow,including control mechanisms by coupled processes,initial states,boundary conditions and hydraulic properties.The effects of each mechanism on seepage control are illustrated with examples in hydroelectric engineering and radioactive waste disposal,and hence the reasonability of classification is demonstrated.Advice on performance assessment and optimization design of the seepage control systems in geotechnical engineering is provided,and the suggested procedure would serve as a useful guidance for cost-effective control of seepage flow in various engineering practices.

More relaxed conditions for model predictive control with guaranteed stability

For the model predictive controller, terminal state satisfying a certain inequality can guarantee the stability but it is somewhat conservative. In this paper, we give a more relaxed stability condition by considering the effect of the initial state. Based on that we propose an algorithm to guarantee that the closed loop system is asymptotically stable. Finally, the conclusions are verified by a simttlation.

Arranging transient process used in iterative learning control system

Considering the same initial state error in each repetitive operation in the iterative learning system, a method of arranging the transient process is given. During the current iteration, the system will track the transient function firstly, and then the expected trajectory. After several iterations, the learning system output will trend to the arranged curve, which has avoided the effect of the initial error on the controller. Also the transient time can be changed as you need, which makes the designing simple and the operation easy. Then the detailed designing steps are given via the robot system. At last the simulation of the robot system is given, which shows the validity of the method.

Theoretical prediction of the optimal conditions for observing the stereodynamical vector properties of the C(~3P) + OH(X^2Π) → CO(X^1 Σ^+) + H(~2S) reaction

The best optimal initial reactant state and collision energy for observing the stereodynamical vector properties of the title reaction in the ground electronic state X2A’ potential energy surface （PES）[Zanchet et al. 2006 J. Phys. Chem. A 110 12017] are theoretically predicted using the quasi-classical trajectory （QCT） method for the first time. The calculated results reveal that the smallest value of the rotational quantum number j, larger vibrational quantum number v, and the lower strength of collision energy should be selected for offering the most obvious picture about the stereodynamical vector properties. Polarization-dependent differential cross sections and the angular momentum alignment distribution, P（θr） and P（Φr） in the center-of-mass frame, are obtained to gain an insight into the alignment and orientation of the product molecules. The rotational angular momentum vector j’ of CO is aligned to be perpendicular to reagent relative velocity k. The product polarizations align along the y axis, pointing to the positive direction of the y axis. A new method is developed to investigate massive reactions with various initial states and to further study the vector properties of the fundamental reactions in detail.

Influence of the initial transient state of plasma and hydrogen pre-treatment on the interface properties of a silicon heterojunction fabricated by PECVD

Amorphous/crystalline silicon heterojunctions（a-Si：H/c-Si SHJ） were prepared by plasma-enhanced chemical vapor deposition（PECVD）.The influence of the initial transient state of the plasma and the hydrogen pre-treatment on the interfacial properties of the heteroj unctions was studied.Experimental results indicate that： （1） The instability of plasma in the initial stage will damage the surface of c-Si.Using a shutter to shield the substrate for 100 s from the starting discharge can prevent the influence of the instable plasma process on the Si surface and also the interface between a-Si and c-Si.（2） The effect of hydrogen pre-treatment on interfacial passivation is constrained by the extent of hydrogen plasma bombardment and the optimal time for hydrogen pre-treatment is about 60 s.

Dynamic constitutive model for soils considering asymmetry of skeleton curve

Based on the asymmetric characteristic of skeleton curve obtained from dynamic tests on soils,a function with double asymptotes is proposed for describing the dynamic constitutive relations of soils.The hysteresis loops observed during unloading and reloading show the same form as the skeleton curve and are constructed by taking the ultimate stress as the corresponding asymptote.The coeffcient of initial unloading modulus is used to ensure that the constructed hysteresis loop fts well with the experimental data.Then,a new dynamic constitutive model considering the asymmetry of skeleton curve is elaborated.The verifcation tests on saturated Nanjing fne sand are performed using a hollow cylinder apparatus to verify the applicability of the UD model.It is found that the predicted curves by the UD model agree well with the test data.

Neural Network State Learning Based Adaptive Terminal ILC for Tracking Iteration-varying Target Points

Terminal iterative learning control(TILC) is developed to reduce the error between system output and a fixed desired point at the terminal end of operation interval over iterations under strictly identical initial conditions. In this work, the initial states are not required to be identical further but can be varying from iteration to iteration. In addition, the desired terminal point is not fixed any more but is allowed to change run-to-run. Consequently, a new adaptive TILC is proposed with a neural network initial state learning mechanism to achieve the learning objective over iterations. The neural network is used to approximate the effect of iteration-varying initial states on the terminal output and the neural network weights are identified iteratively along the iteration axis.A dead-zone scheme is developed such that both learning and adaptation are performed only if the terminal tracking error is outside a designated error bound. It is shown that the proposed approach is able to track run-varying terminal desired points fast with a specified tracking accuracy beyond the initial state variance.