Momentum space distribution of electrons in an atom using hydrogenic wave functions

A formulation is developed to derive exact analytic expressions for electron-electron correlation and density of electrons in momentum space using hydrogenic wave functions. It is shown that for large atoms the expression for density of electrons has a simple form.     

Bianchi Type V Magnetized String Dust Bulk Viscous Fluid Cosmological Model with Variable Magnetic Permeability

Bianchi Type V magnetized string dust bulk viscous fluid cosmological model with variable magnetic permeability, is investigated. The magnetic field is due to an electric current produced along x-axis. Thus the magnetic fields is in yz-plane and F ₂₃ is the only non-vanishing component of electromagnetic field tensor F _ij . To get the deterministic model in terms of cosmic time t, we have also assumed the condition ζ θ=constant where ζ the coefficient of bulk viscosity and θ the expansion in the model. The behaviour of the model in presence and absence of magnetic field and bulk viscosity and singularities in the model are also discussed.      

Dynamics of electricity market correlations

Electricity market participants rely on demand and price forecasts to decide their bidding strategies, allocate assets, negotiate bilateral contracts, hedge risks, and plan facility investments. However, forecasting is hampered by the non-linear and stochastic nature of price time series. Diverse modeling strategies, from neural networks to traditional transfer functions, have been explored. These approaches are based on the assumption that price series contain correlations that can be exploited for model-based prediction purposes. While many works have been devoted to the demand and price modeling, a limited number of reports on the nature and dynamics of electricity market correlations are available. This paper uses detrended fluctuation analysis to study correlations in the demand and price time series and takes the Australian market as a case study. The results show the existence of correlations in both demand and prices over three orders of magnitude in time ranging from hours to months. However, the Hurst exponent is not constant over time, and its time evolution was computed over a subsample moving window of 250 observations. The computations, also made for two Canadian markets, show that the correlations present important fluctuations over a seasonal one-year cycle. Interestingly, non-linearities (measured in terms of a multifractality index) and reduced price predictability are found for the June-July periods, while the converse behavior is displayed during the December-January period. In terms of forecasting models, our results suggest that non-linear recursive models should be considered for accurate day-ahead price estimation. On the other hand, linear models seem to suffice for demand forecasting purposes.     

Subgroups of index 4 of the 2-dimensional space groups

There are 281 subgroups of index 4 for the 17 types of 2-dimension space groups: p1:7, p2:31, pm:19, pg:7, cm:11, p2mm:67, p2mg:23, p2gg:11, c2mm:31, p4:11, p4mm:31, p4gm:11, p3:4, p3m1:4, p31m:4, p6:4, p6mm:5. Every subgroup has been identified by its conventional cell disposition with respect to the conventional cell of the starting group. These subgroups may be arranged in 96 automorphism classes and 184 conjugation classes according to their starting groups.     

Fractional motions

Brownian motion is the archetypal model for random transport processes in science and engineering. Brownian motion displays neither wild fluctuations (the “Noah effect”), nor long-range correlations (the “Joseph effect”). The quintessential model for processes displaying the Noah effect is Lévy motion, the quintessential model for processes displaying the Joseph effect is fractional Brownian motion, and the prototypical model for processes displaying both the Noah and Joseph effects is fractional Lévy motion. In this paper we review these four random-motion models–henceforth termed “fractional motions” –via a unified physical setting that is based on Langevin’s equation, the Einstein–Smoluchowski paradigm, and stochastic scaling limits. The unified setting explains the universal macroscopic emergence of fractional motions, and predicts–according to microscopic-level details–which of the four fractional motions will emerge on the macroscopic level. The statistical properties of fractional motions are classified and parametrized by two exponents—a “Noah exponent” governing their fluctuations, and a “Joseph exponent” governing their dispersions and correlations. This self-contained review provides a concise and cohesive introduction to fractional motions.     

参数型Marcinkiewicz积分交换子在Hardy空间的有界性(英文)

研究了参数型Marcinkiewicz积分高阶交换子并证明了其从H1b(Rn)到L1(Rn)有界,其中b∈BMO.     

Phase space density representations in fluid dynamics

Phase space density representations of inviscid fluid dynamics were recently discussed by Abarbanel and Rouhi. Here it is shown that such representations may be simply derived and interpreted by means of the Liouville equation corresponding to the dynamical system of ordinary differential equations that describes fluid particle trajectories. The Hamiltonian and Poisson bracket for the phase space density then emerge as immediate consequences of the corresponding structure of the dynamics. For barotropic fluids, this approach leads by direct construction to the formulation presented by Abarbanel and Rouhi. Extensions of this formulation to inhomogeneous incompressible fluids and to fluids in which the state equation involves an additional transported scalar variable are constructed by augmenting the single-particle dynamics and phase space to include the relevant additional variable.     

Investigating generation mechanisms of tyre/road noise by speed exponent analysis

The purpose of this study is to clarify the influence of air-pumping related noise sources on typical tyre/road noise. The aim is to increase the understanding of noise generation mechanisms and catalyse the development of existing tyre/road noise simulation tools. The speed dependency of measured and simulated tyre/road noise is analysed and the results show that a large part of the noise can be explained by a high speed exponent traditionally connected with air-pumping mechanisms. Surprisingly, this is also the case for rough road surfaces which are expected to mainly generate noise by tyre vibrations. It is also found that vehicle wind noise may have a strong influence on the pass-by noise and care must be taken when analysing measurement data of quiet tyre/road combinations. Even simulated tyre/road noise shows higher speed exponents than what is anticipated without the inclusion of any type of air-pumping mechanism in the model. It is concluded that it is unfeasible to separate noise created by tyre vibrations from noise created by air-pumping with a speed exponent analysis due to the overlap in the speed exponents connected with the different generation mechanisms.