Self-adaptive difference method for the effective solution of computationally complex problems of boundary layer theory

An implicit difference procedure for the solution of equations for a chemically reacting hypersonic boundary layer is described. Difference forms of arbitrary error order in the x and y coordinate plane were used to derive estimates for discretization error. Computational complexity and time were minimized by the use of this difference method and the iteration of the nonlinear boundary layer equations was regulated by discretization error. Velocity and temperature profiles are presented for Mach 20.14 and Mach 18.5; variables are velocity profiles, temperature profiles, mass flow factor, Stanton number, and friction drag coefficient; three figures include numeric data

Advanced resistivity model for arbitrary magnetization orientation applied to a series of compressive- to tensile-strained (Ga,Mn)As layers

The longitudinal and transverse resistivities of differently strained (Ga,Mn)As layers are theoretically and experimentally studied as a function of the magnetization orientation. The strain in the series of (Ga,Mn)As layers is gradually varied from compressive to tensile using (In,Ga)As templates with different In concentrations. Analytical expressions for the resistivities are derived from a series expansion of the resistivity tensor with respect to the direction cosines of the magnetization. In order to quantitatively model the experimental data, terms up to the fourth order have to be included. The expressions derived are generally valid for any single-crystalline cubic and tetragonal ferromagnet and apply to arbitrary surface orientations and current directions. The model phenomenologically incorporates the longitudinal and transverse anisotropic magnetoresistance as well as the anomalous Hall effect. The resistivity parameters obtained from a comparison between experiment and theory are found to systematically vary with the strain in the layer.Comment: 14 pages, 11 figures, submitted to Phys. Rev.

Generation of phase-coherent states

An interaction scheme involving nonlinear $\chi^{(2)}$ media is suggested for the generation of phase-coherent states (PCS). The setup is based on parametric amplification of vacuum followed by up-conversion of the resulting twin-beam. The involved nonlinear interactions are studied by the exact numerical diagonalization. An experimentally achievable working regime to approximate PCS with high conversion rate is given, and the validity of parametric approximation is discussed.Comment: To appear in PRA -- More info at http://enterprise.pv.infn.it

Individual and Neighborhood Determinants of Survey Nonresponse – An Analysis Based on a New Subsample of the German Socio-Economic Panel (SOEP), Microgeographic Characteristics and Survey-Based Interviewer Characteristics

This study examines the phenomenon of nonresponse in the first wave of a refresher sample (subsample H) of the German Socio-Economic Panel Study (SOEP). Our first step is to link additional (commercial) microgeographic data on the immediate neighborhoods of the households visited by interviewers. These additional data (paradata) provide valuable information on respondents and nonrespondents, including milieu or lifestyle, dominant household structure, desire for anonymity, frequency of moves, and other important microgeographic information. This linked information is then used to analyze nonresponse. In a second step, we also use demographic variables for the interviewer from an administrative data set about the interviewers, and, in a third step, we use the results of a special interviewer survey. We use multilevel statistical modeling to examine the influence of neighborhoods and interviewers on non-contacts, inability to participate, and refusals. In our analysis, we find our additional variables useful for understanding and explaining non-contacts and refusals and the inability of some respondents to participate in surveys. These data provide an important basis for filling the information gap on response and nonresponse in panel surveys (and in cross-sectional surveys). However, the effect sizes of these effects are negligible. Ignoring these effects does not cause significant biases in statistical inferences drawn from the survey under consideration