Symmetry-breaking and chaos in electron transport in semiconductor superlattices

We study the motion of electrons in a single miniband of a semiconductor superlattice driven by THz electric field polarized along the growth direction. We work in the semiclassical balance-equation model, including different elastic and inelastic scattering rates, and incorporating the self-consistent electric field generated by electron motion. We explore regions of complex dynamics, which can include chaotic behaviour and symmetry-breaking. We estimate the magnitudes of dc current and dc voltage that spontaneously appear in regions of broken-symmetry for parameters characteristic of modern semiconductor superlattices. This work complements PRL 80(1998)2669 [ cond-mat/9709026 ].

Example-Based Image Restoration via Boosted Classifiers

We propose a novel image registration framework which uses classifiers trained from examples of aligned images to achieve registration. Our approach is designed to register images of medical data where the physical condition of the patient has changed significantly and image intensities are drastically different. We use two boosted classifiers for each degree of freedom of image transformation. These two classifiers can both identify when two images are correctly aligned and provide an efficient means of moving towards correct registration for misaligned images. The classifiers capture local alignment information using multi-pixel comparisons and can therefore achieve correct alignments where approaches like correlation and mutual-information which rely on only pixel-to-pixel comparisons fail. We test our approach using images from CT scans acquired in a study of acute respiratory distress syndrome. We show significant increase in registration accuracy in comparison to an approach using mutual information.