Topological defect lasers

We demonstrate topological defect lasers in a GaAs membrane with embedded InAs quantum dots. By introducing a disclination to a square-lattice of elliptical air holes, we obtain spatially confined optical resonances with high quality factor. Such resonances support powerflow vortices, and lase upon optical excitation of quantum dots, embedded in the structure. The spatially inhomogeneous variation of the unit cell orientation adds another dimension to the control of a lasing mode, enabling the manipulation of its field pattern and energy flow landscape

On the Structure of Measurement Noise in Eye-Tracking

Past research has discovered fractal structure in eye movement variability and interpreted this result as having theoretical ramifications. No research has, however, investigated how properties of the eye-tracking instrument might affect the structure of measurement varia-bility. The current experiment employed fractal and multifractal methods to investigate whether an eye-tracker produced intrinsic random variation and how features of the data recording procedure affected the structure measurement variability. The results of this experiment revealed that the structure of variation from a fake eye was indeed random and uncorrelated in contrast to the fractal structure from a fixated, real human eye. Moreover, the results demonstrated that data-averaging generally changes the structure of variation, introducing spurious structure into eye movement variability

Is the `IR Coincidence' Just That?

(Abridged) Motch (1985) suggested that in the hard state of GX 339-4 the soft X-ray power-law extrapolated backward in energy agrees with the IR flux. Corbel & Fender (2002) showed that the hard state radio power-law extrapolated forward in energy meets the extrapolated X-ray power-law at an IR break, which was explicitly observed twice in GX 339-4. This `IR coincidence' has been cited as further evidence that a jet might make a significant contribution to the X-rays in hard state systems. We explore this hypothesis with a series of simultaneous radio/X-ray observations of GX 339-4, taken during its 1997, 1999, and 2002 hard states. We fit these spectra, in detector space, with a simple, but remarkably successful, doubly broken power-law that requires an IR spectral break. For these observations, the break position and the integrated radio/IR flux have stronger dependences upon the X-rays than the simplest jet predictions. If one allows for a softening of the X-ray power law with increasing flux, then the jet model agrees with the correlation. We also find evidence that the radio/X-ray fcorrelation previously observed in GX 339-4 shows a `parallel track' for the 2002 hard state. The slope of the 2002 correlation is consistent with prior observations; however, the radio amplitude is reduced. We then examine the correlation in Cyg X-1 through the use of radio data, obtained with the Ryle radio telescope, and RXTE data, from the ASM and pointed observations. We again find evidence of `parallel tracks', and here they are associated with `failed transitions' to the soft state. We also find that for Cyg X-1 the radio flux is more fundamentally correlated with the hard X-ray flux.Comment: To Appear in the July 2005 Astrophysical Journal; 9 Pages, uses emulateapj.st

Modeling Collective Animal Behavior with a Cognitive Perspective: A Methodological Framework

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters

Application of Low-Cost UASs and Digital Photogrammetry for High-Resolution Snow Depth Mapping in the Arctic

The repeat acquisition of high-resolution snow depth measurements has important research and civil applications in the Arctic. Currently the surveying methods for capturing the high spatial and temporal variability of the snowpack are expensive, in particular for small areal extents. An alternative methodology based on Unmanned Aerial Systems (UASs) and digital photogrammetry was tested over varying surveying conditions in the Arctic employing two diverse and low-cost UAS-camera combinations (500 and 1700 USD, respectively). Six areas, two in Svalbard and four in Greenland, were mapped covering from 1386 to 38,410 m2. The sites presented diverse snow surface types, underlying topography and light conditions in order to test the method under potentially limiting conditions. The resulting snow depth maps achieved spatial resolutions between 0.06 and 0.09 m. The average difference between UAS-estimated and measured snow depth, checked with conventional snow probing, ranged from 0.015 to 0.16 m. The impact of image pre-processing was explored, improving point cloud density and accuracy for different image qualities and snow/light conditions. Our UAS photogrammetry results are expected to be scalable to larger areal extents. While further validation is needed, with the inclusion of extra validation points, the study showcases the potential of this cost-effective methodology for high-resolution monitoring of snow dynamics in the Arctic and beyond