Selection-Based Learning: The Coevolution Of Internal And External Selection In High-Velocity Environments

To understand the effects of selection on firm-level learning, this study synthesizes two contrasting views of evolution. Internal selection theorists view managers in multiproduct firms as the primary agents of evolutionary change because they decide whether individual products and technologies are retained or eliminated. In contrast, external selection theorists contend that the environment drives evolution because it determines whether entire firms live or die. Though these theories differ, they describe tightly interwoven processes. In assessing the coevolution of internal and external selection among personal computer manufacturers across a 20-year period, we found that (1) firms learned cumulatively and adaptively from internal and partial external selection, the latter occurring when the environment killed part but not all of a firm; (2) internal and partial external selection coevolved, as each affected the other's future rate and the odds of firm failure; (3) partial external selection had a greater effect on future outcomes than internal selection; and (4) the lessons gleaned from prior selection were reflected in a firm's ability to develop new products, making that an important mediator between past and future selection events.Managemen

Poincaré maps define topography of Vlasov distribution functions consistent with stochastic dynamics

In a recent paper [A. D. Bailey et al., Phys. Rev. Lett. 34, 3124 (1993)], the authors presented direct planar laser induced fluorescence measurements of the oscillatory ion fluid velocity field in the presence of a large amplitude drift-Alfven wave. Surprisingly, the measured speeds were an order of magnitude lower than predicted by standard fluid theory, yet the flow pattern was consistent with the fluid theory. A new model, based on the connection between stochasticity and bulk behavior, is presented which gives insights into the cause of this behavior. It is shown that when particle motion is stochastic, invariant sets of a 'Poincaré map' define a flat-topped particle distribution function consistent with both the electromagnetic field driving the Vlasov equation and the fine-scale single particle dynamics. The approach is described for the general case and explored for a slab model of the observed drift wave

Dual Instantons

We show how to map the Belavin-Polyakov instantons of the O(3)-nonlinear $\sigma-$model to a dual theory where they then appear as nontopological solitons. They are stationary points of the Euclidean action in the dual theory, and moreover, the dual action and the O(3)-nonlinear $\sigma-$model action agree on shell.Comment: 13 page

Drift and Diffusion of Spins Generated by the Spin Hall Effect

Electrically generated spin accumulation due to the spin Hall effect is imaged in n-GaAs channels using Kerr rotation microscopy, focusing on its spatial distribution and time-averaged behavior in a magnetic field. Spatially-resolved imaging reveals that spin accumulation observed in transverse arms develops due to longitudinal drift of spin polarization produced at the sample boundaries. One- and two-dimensional drift-diffusion modeling is used to explain these features, providing a more complete understanding of observations of spin accumulation and the spin Hall effect.Comment: 9 pages, 3 figure

Empirical modeling of the quiet time nightside magnetosphere

Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko (1989) but is modified by the addition of an inner eastward ring current at a radial distance of ∼3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko (1987) such that the former dominates the magnetic field in the inner magnetosphere, whereas the latter prevails in the distant tail. The distribution of plasma pressure, which is required to balance the magnetic force for each of these two field models, is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This effort is the first attempt to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of ∼3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between ∼2 and ∼35 RE