How Will a Particle Detector Respond in Massless Complex Scalar Field？

I study the response of a particle detector coupled to quantized massless complex scalar field in four dimensional Minkowski spacetime through nonlinear Lagrangian. I find that as in the real scalar field： the particle detector will not respond when it is in inertial motion; If accelerated in its own frame reference, it does respond and feel the same temperature. But different from the real scalar field case, the detector＇s transition amplitude is concerned with particle-antiparticle creation, and the response of the detector is （1/α^2 ＋ ε^2）/24π^2 times of that in real scalar field, with 1/α the accelerator of the detector and e the energy gap between the detector＇s two energy level. It is due to the nonlinear property of the coupling Lagrangian. Whether the total charge of the system constructed by the particle detector and vacuum is conserved is also considered and analyzed.     

Stability analysis of Markovian jumping stochastic Cohen Grossberg neural networks with discrete and distributed time varying delays

In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen-Grossberg neural networks with discrete and distributed time-varying delays （MJSCGNNs） is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen-Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples.     

Studies of dE/dx measurements with the BESⅢ

The Beijing Spectrometer Ⅲ（BESⅢ）is a general-purpose detector used for the study of τ-charm physics at the Beijing Electron-Positron Collider Ⅱ（BEPC Ⅱ）.This paper presents our studies of the dE/dx measurement in the drift chamber of BESⅢ,which is important for the identification of charged particles.Corrections applied to the dE/dx measurement in data reconstruction are discussed.After our current dE/dx calibration,a resolution of about 6% has been obtained for minimum ionization particles,and a 3σ K/πseparation is obtained for momenta up to 760 MeV/c.These results meet the design goals of the BESⅢ drift chamber.     

Pattern recognition and data mining software based on artificial neural networks applied to proton transfer in aqueous environments

In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories： transfer ＇occurred＇ and transfer ＇not occurred＇. The goal of this paper is to evaluate the use of artificial neural networks in the classification of proton transfer events, based on the feed-forward back propagation neural network, used as a classifier to distinguish between the two transfer cases. In this paper, we use a new developed data mining and pattern recognition tool for automating, controlling, and drawing charts of the output data of an Empirical Valence Bond existing code. The study analyzes the need for pattern recognition in aqueous proton transfer processes and how the learning approach in error back propagation （multilayer perceptron algorithms） could be satisfactorily employed in the present case. We present a tool for pattern recognition and validate the code including a real physical case study. The results of applying the artificial neural networks methodology to crowd patterns based upon selected physical properties （e.g., temperature, density） show the abilities of the network to learn proton transfer patterns corresponding to properties of the aqueous environments, which is in turn proved to be fully compatible with previous proton transfer studies.     

Knotted Picture of Unknown Quantum State in Process of Quantum Teleportation

This paper gives the knotted picture of the unknown quantum state in the process of quantum teleportation and the surgical knotted operations of the unitary operators operated on the teleported quantum state.     

Experimental identification of a comb-shaped chaotic region in multiple parameter spaces simulated by the Hindmarsh–Rose neuron model

A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh-Rose （HR） neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two- dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the determin- istic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in dif- ferent two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces.     

New test and analysis of position-sensitive-silicon-detector

We have tested and analyzed the properties of two-dimensional Position-Sensitive-silicon-Detector （PSD） with new integrated preamplifiers. The test demonstrates that the best position resolution for 5.5 MeV α particles is 1.7 mm （FWHM）, and the best energy resolution is 2.1%, which are notably better than the previously reported results. A scaling formula is introduced to make the absolute position calibration.     

Effects of material properties on the competition mechanism of heat transfer of a granular bed in rotary cylinders

Mixing and heat transfer processes of the granular materials within rotary cylinders play a key role in industrial processes. The numerical simulation is carried out by using the discrete element method (DEM) to investigate the influences of material properties on the bed mixing and heat transfer process, including heat conductivity, heat capacity, and shear modulus. Moreover, a new Pe′clet number is derived to determine the dominant mechanism of the heating rate within the particle bed, which is directly related to thermal and mechanical properties. The system exhibits a faster heating rate with the increase of ratio of thermal conductivity and heat capacity, or the decrease of shear modulus when inter-particle conduction dominates the heating rate; conversely, it shows a fast-mixing bed when particle convection governs the heating rate. The simulation results show good agreement with the theoretical predictions.     

H∞ synchronization of chaotic neural networks with time-varying delays

In this paper,we investigate the problem of H∞ synchronization for chaotic neural networks with time-varying delays.A new model of the networks with disturbances in both master and slave systems is presented.By constructing a suitable Lyapunov–Krasovskii functional and using a reciprocally convex approach,a novel H∞ synchronization criterion for the networks concerned is established in terms of linear matrix inequalities(LMIs)which can be easily solved by various effective optimization algorithms.Two numerical examples are given to illustrate the effectiveness of the proposed method.     

DD proton spectrum for diagnosing the areal density of imploded capsules on Shenguang III prototype laser facility

The primary DD proton spectrum is used for diagnosing the fuel-shell areal density pR of imploded capsules on Shenguang Ⅲ （SG-Ⅲ） prototype laser facility for the first time. A charged particle spectrometer （CPS） with a CR39 nuclear track detector is used to measure the DD proton spectrum. The proton spectrum is determined from both the proton track and its size. A typical proton energy peak shift from 3.02 MeV to 2.6 MeV is observed in our experiment, which yields a maximum pR larger than 6 mg/cm2.     

Study of pre-scission particle emissions and fission probability of the l78W produced in fusion reactions

A dynamical model based on one-dimensional Langevin equations was used to calculate the average pre-fission multiplicities of neutrons, light charged particles, and the fission probability for compound nucleus 17Sw produced in fusion reactions. The pre-seission multiplicities of particles and fission probability are calculated and compared with the experimental data over a wide range of excitation energy. A modified wall and window dissipation with a reduction coefficient, ks, has been used in the Langevin equations for reproducing experimental data. It was shown that the results of the calculations are in good agreement with the experimental data by using values of ks in the range 0.24〈 ks 〈0.47.     

Application of the HKS in the identification of kaons produced in the reaction （e,e＇K^＋）

At Jefferson Laboratory the experiment E02-017 was carried out to investigate the fission associated with kaons in the hypernuclei-producing interaction p（e,K^＋e＇）A. The newly installed high resolution kaon spectrometer （HKS） in Hall C was used as a key instrument to identify kaons. This paper introduces the HKS hardware and describes the way the kaons are identified. Maintaining most of the kaons （nearly 100%） in the data, HKS identifies kaons with a purity of -67% in this experiment. The resolution of the kaon target time reconstructed by HKS reaches 0.42 ns.     

y2-y∞learnlngof dynamic neural.networks

This paper proposes an y2-y∞ learning law as a new learning method for dynamic neural networks with external disturbance. Based on linear matrix inequality （LMI） formulation, the y2-y∞ learning law is presented to not only guarantee asymptotical stability of dynamic neural networks but also reduce the effect of external disturbance to an y2-y∞ induced norm constraint. It is shown that the design of the y2-y∞ learning law for such neural networks can be achieved by solving LMIs, which can be easily facilitated by using some standard numerical packages. A numerical example is presented to demonstrate the validity of the proposed learning law.     

Quantum Secure Direct Communication with Four-Particle Genuine Entangled State and Dense Coding

A quantum secure direct communication scheme using dense coding is proposed. At first, the sender （Alice） prepares four-particle genuine entangled states and shares them with the receiver （Bob） by sending two particles in each entangled state to him. Secondly, Alice encodes secret information by performing the unitary transformations on her particles and transmits them to Bob. Finally, Bob performs the joint measurements on his particles to decode the secret information. The two-step security test guarantees the security of communication.     

Test particle simulations of resonant interactions between energetic electrons and discrete,multi-frequency artificial whistler waves in the plasmasphere

Modulated high frequency(HF) heating of the ionosphere provides a feasible means of artificially generating extremely low frequency(ELF)/very low frequency(VLF) whistler waves, which can leak into the inner magnetosphere and contribute to resonant interactions with high energy electrons. Combining the ray tracing method and test particle simulations, we evaluate the effects of energetic electron resonant scattering driven by the discrete, multi-frequency artificially generated ELF/VLF waves. The simulation results indicate a stochastic behavior of electrons and a linear profile of pitch angle and kinetic energy variations averaged over all test electrons. These features are similar to those associated with single-frequency waves. The computed local diffusion coefficients show that, although the momentum diffusion of relativistic electrons due to artificial ELF/VLF whistlers with a nominal amplitude of ～ 1 pT is minor, the pitch angle scattering can be notably efficient at low pitch angles near the loss cone, which supports the feasibility of artificial triggering of multi-frequency ELF/VLF whistler waves for the removal of high energy electrons from the magnetosphere. We also investigate the dependences of diffusion coefficients on the frequency interval(△f) of the discrete, multi-frequency waves.We find that there is a threshold value of △f for which the net diffusion coefficient of multi-frequency whistlers is inversely proportional to △f(proportional to the frequency components Nw) when △f is below the threshold value but it remains unchanged with increasing △f when △f is larger than the threshold value. This is explained as being due to the fact that the resonant scattering effect of broadband waves is the sum of the effects of each frequency in the ‘effective frequency band’. Our results suggest that the modulation frequency of HF heating of the ionosphere can be appropriately selected with reasonable frequency intervals so that better performance of controlled precipitation of high energy electrons in the plasmasphere by artificial ELF/VLF whistler waves can be achieved.     

Source identification of individual P M2.5 particles in Shanghai air in the winter of 2007 with synchrotron X-ray fluorescence microprobe

In order to further understand the sources of PM2.5 in Shanghai air, the synchrotron X-ray fluores- cence microprobe at the BL-4A Beamline of Photon Factory of High Energy Accelerator Research Organization, Japan, was applied to analyze the individual PM2.5 particles collected from Shanghai air in the winter of 2007. Eight categories of emission sources were recognized in these individual particles. The source identification shows that most of the analyzed PM2.5 particles are derived from vehicle exhaust and metallurgical emissions. This suggests that the important emission sources of PM2.5 in Shanghai air would be vehicle exhaust and metallurgical activities.     

Effects of Coupling Distance on Synchronization and Coherence in Chaotic Neural Networks

Effects of coupling distance on synchronization and coherence of chaotic neurons in complex networks are numerically investigated. We find that it is not beneficial to neurons synchronization if confining the coupling distance of random edges to a limit dmax, but help to improve their coherence. Moreover, there is an optimal value of dmax at which the coherence is maximum.     

Large Number, Dark Matter, Dark Energy, and Superstructures in the Universe

Since there may exist dark matter particles ν and δ with mass - 10^-1 e V in the universe, the superstructures with a scale of 10^19 solar masses （large number A - 10^19） appeared during the era near and before the hydrogen recombination. Since there are superstructures in the universe, there may be no necessity for the existence of dark energy. For checking the superstructure in the universe by CMB anisotropy, we need to measure CMB angular power spectrum especially around ten degrees across the sky- in more details, While neutrino u is related to electroweak unification, the fourth stable elementary particle 6 may be related to strong-gravity unification, which suggests p ＋ p^- → n ＋ δ^- and that some new baryons appeared in the TeV region.     

Dynamic investigation of the finite dissolution of silicon particles in aluminum melt with a lower dissolution limit

The finite dissolution model of silicon particles in the aluminum melt is built and calculated by the finite difference method, and the lower dissolution limit of silicon particles in the aluminum melt is proposed and verified by experiments, which could be the origin of microinhomogeneity in aluminum-silicon melts. When the effects of curvature and interface reaction on dissolution are not considered; the dissolution rate first decreases and later increases with time. When the effects of curvature and interface reaction on dissolution are considered, the dissolution rate first decreases and later increases when the interface reaction coefficient （k） is larger than 10 1, and the dissolution rate first decreases and later tends to be constant when k is smaller than 10-3. The dissolution is controlled by both diffusion and interface reaction when k is larger than 10-3, while the dissolution is controlled only by the interface reaction when k is smaller than 10-4.     

Unified description of angular distributions of target particles in light and heavy ion induced interactions in nuclear emulsions at high energies

Some investigations show that in light ion （LI） induced reactions, such as He, O, Ne, and Ar in nuclear emulsions （Em） at high energies, the angular distributions of the target particles show a wide structure around the polar angle V ≈ 60°. With heavy ions （HI） such as Kr and Au such a wide structure has not been observed. The experimental results on Mg-Em and Si-Em interactions also do not show such a wide structure in the angular distribution of the target particles. Using a multisource ideal gas model we uniformly describe the angular distributions of the target particles produced in LI-Em and HI-Em interactions. The result is not only in agreement with the mean trend, but also with the fluctuations of the experimental data. We conclude that the wide structure observed in LI-Em interactions may be the result of statistical fluctuations.