Determination of femtosecond-laser-induced refractive-index changes in an optical fiber from far-field measurements.

A new method for direct writing of localized, circularly symmetric refractive-index changes in optical fibers with a femtosecond laser is demonstrated. The refractive-index changes are characterized using a novel approach employing comparison of numerical simulations to the measured far-field profiles of unmodified and modified fibers. From the analysis, a negative refractive-index change of -0.015±0.005 within a radius of (0.6±0.1) µm is determined.

Measurement of effective refractive-index differences in a few-mode fiber by axial fiber stretching.

A method for measuring the effective refractive-index differences in a few-mode fiber by applying axial fiber stretching is described. This method represents a straightforward technique for characterization of few-mode fibers. Interference between LP01 and LP11 and in some cases also between LP11 and LP21 are observed in a fiber designed for support of LP01 and LP11. The relative strength of the coupled modes depends on specific splicing characteristics, and in some cases only two modes are seen. The results agree well with theoretical predictions for the fiber under investigation.

Effect of thresholding on avalanches and their clustering for interfaces with long-range elasticity.

Avalanches are often defined as signals higher than some detection level in bursty systems. The choice of the detection threshold affects the number of avalanches, but it can also affect their temporal correlations. We simulated the depinning of a long-range elastic interface and applied different thresholds including a zero one on the data to see how the sizes and durations of events change and how this affects temporal avalanche clustering. Higher thresholds result in steeper size and duration distributions and cause the avalanches to cluster temporally. Using methods from seismology, the frequency of the events in the clusters was found to decrease as a power-law of time, and the size of an event in a cluster was found to help predict how many events it is followed by. The results bring closer theoretical studies of this class of models to real experiments, but also highlight how different phenomena can be obtained from the same set of data.

Complementarity in Requirements Tracing.

Complementarity between activities reveals that doing any one of them increases the returns to doing the others. In other words, complementarity leads to the synergistic effect that the whole is greater than the sum of its parts. Identifying and exploiting complementarity can benefit many cybernetic activities, where human-machine interactions are inherent and dominant. One such activity is requirements tracing that helps stakeholders to track the status of their goals. Although various kinds of support for human analysts in requirements tracing have been proposed, little is known about the nature of complementarity when different tracing practices are involved. In this paper, we explore the role of complementarity by considering together the tagging-to-trace (T2T) and learning-to-trace (L2T) activities. We present a novel approach to examining which T2T and L2T practices enhance the qualities of each other. Our approach also uncovers the environmental factors which the complementarity is sensitive to. Applying our approach to the logs of 140 analyst-tracing units offers operational insights into the rigorous detection of complementarity and shows the importance of understanding the cybernetic conditions under which the requirements tracing practices may in fact be complementary.