The effect of continuous, nonlinearly transformed visual feedback on rapid aiming movements

We investigated the ability to adjust to nonlinear transformations that allow people to control external systems like machines and tools. Earlier research (Verwey and Heuer 2007) showed that in the presence of just terminal feedback participants develop an internal model of such transformations that operates at a relatively early processing level (before or at amplitude specification). In this study, we investigated the level of operation of the internal model after practicing with continuous visual feedback. Participants executed rapid aiming movements, for which a nonlinear relationship existed between the target amplitude seen on the computer screen and the required movement amplitude of the hand on a digitizing tablet. Participants adjusted to the external transformation by developing an internal model. Despite continuous feedback, explicit awareness of the transformation did not develop and the internal model still operated at the same early processing level as with terminal feedback. Thus with rapid aiming movements, the type of feedback may not matter for the locus of operation of the internal model

Effects of Short Range Correlations on Ca Isotopes

The effect of Short Range Correlations (SRC) on Ca isotopes is studied using a simple phenomenological model. Theoretical expressions for the charge (proton) form factors, densities and moments of Ca nuclei are derived. The role of SRC in reproducing the empirical data for the charge density differences is examined. Their influence on the depletion of the nuclear Fermi surface is studied and the fractional occupation probabilities of the shell model orbits of Ca nuclei are calculated. The variation of SRC as function of the mass number is also discussed.Comment: 11 pages (RevTex), 6 Postscript figures available upon request at [email protected] Physical Review C in prin

Power-law distributions for the areas of the basins of attraction on a potential energy landscape

Energy landscape approaches have become increasingly popular for analysing a wide variety of chemical physics phenomena. Basic to many of these applications has been the inherent structure mapping, which divides up the potential energy landscape into basins of attraction surrounding the minima. Here, we probe the nature of this division by introducing a method to compute the basin area distribution and applying it to some archetypal supercooled liquids. We find that this probability distribution is a power law over a large number of decades with the lower-energy minima having larger basins of attraction. Interestingly, the exponent for this power law is approximately the same as that for a high-dimensional Apollonian packing, providing further support for the suggestion that there is a strong analogy between the way the energy landscape is divided into basins, and the way that space is packed in self-similar, space-filling hypersphere packings, such as the Apollonian packing. These results suggest that the basins of attraction provide a fractal-like tiling of the energy landscape, and that a scale-free pattern of connections between the minima is a general property of energy landscapes.Comment: 4 pages, 3 figure

Characterizing the network topology of the energy landscapes of atomic clusters

By dividing potential energy landscapes into basins of attractions surrounding minima and linking those basins that are connected by transition state valleys, a network description of energy landscapes naturally arises. These networks are characterized in detail for a series of small Lennard-Jones clusters and show behaviour characteristic of small-world and scale-free networks. However, unlike many such networks, this topology cannot reflect the rules governing the dynamics of network growth, because they are static spatial networks. Instead, the heterogeneity in the networks stems from differences in the potential energy of the minima, and hence the hyperareas of their associated basins of attraction. The low-energy minima with large basins of attraction act as hubs in the network.Comparisons to randomized networks with the same degree distribution reveals structuring in the networks that reflects their spatial embedding.Comment: 14 pages, 11 figure