Geometric Scaling Analysis of Deep Inelastic Scattering Data Including Heavy Quarks

An analytic massive total cross section of photon proton scattering is derived, which has geometric scaling. A geometric scaling is used to perform a global analysis of the deep inelastic scattering data on inclusive structure function F2 measured in lepton-hadron scattering experiments at small values of Bjorken x. It is shown that the descriptions of the inclusive structure function F2 and longitudinal structure function FL are improved with the massive analytic structure function, which may imply the gluon saturation effect dominating the parton evolution process at HERA. The inclusion of the heavy quarks prevent the divergence of the lepton-hadron cross section, which plays a significant role in the description of the photoproduction region.

Characteristic Analysis of Underwater Acoustic Scattering Echoes in the Wavelet Transform Domain

Underwater acoustic scattering echoes have time–space structures and are aliasing in time and frequency domains. Different series of echoes properties are not identified when incident angle is unknown. This article investigates variations in target echoes of monostatic sonar to address this problem. The mother wavelet with similar structures has been proposed on the basis of preprocessing signal waveform using matched filter, and the theoretical expressions between delay factor and incident angle are derived in the wavelet domain. Analysis of simulation data and experimental results in free-field pool show that this method can effectively separate geometrical scattering components of target echoes. The time delay estimation obtained from geometrical echoes at a single angle is consistent with target geometrical features, which provides a basis for object recognition without angle information. The findings provide valuable insights for analyzing elastic scattering echoes in actual ocean environment.

A Geometry-Based Non-Stationary MIMO Channel Model for Vehicular Communications

This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals(AOAs) along with the angle of departures(AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function(ACF) and the space cross-correlation functions(CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.