Shot noise in transport through quantum dots: Clean versus disordered samples

We investigate the role of disorder and diffractive scattering in the shot noise power of quantum transport through a two-dimensional quantum dot. By tuning the strength of the disorder potential and the openings of the dot, we numerically explore the influence of quantum scattering mechanisms on the current shot noise. For small cavity openings we find the shot noise for disordered samples to be of almost equal magnitude as for clean samples where transport is ballistic. We explain this finding by diffractive scattering at the cavity openings which act as strong noise sources. Estimates for the shot noise induced by both the disorder potential and the diffractive openings are presented that agree with the numerical data.     

Smooth Image Sequences for Data‐driven Morphing

Smoothness is a quality that feels aesthetic and pleasing to the human eye. We present an algorithm for finding “as‐smooth‐as‐possible” sequences in image collections. In contrast to previous work, our method does not assume that the images show a common 3D scene, but instead may depict different object instances with varying deformations, and significant variation in lighting, texture, and color appearance. Our algorithm does not rely on a notion of camera pose, view direction, or 3D representation of an underlying scene, but instead directly optimizes the smoothness of the apparent motion of local point matches among the collection images. We increase the smoothness of our sequences by performing a global similarity transform alignment, as well as localized geometric wobble reduction and appearance stabilization. Our technique gives rise to a new kind of image morphing algorithm, in which the in‐between motion is derived in a data‐driven manner from a smooth sequence of real images without any user intervention. This new type of morph can go far beyond the ability of traditional techniques. We also demonstrate that our smooth sequences allow exploring large image collections in a stable manner.     

Hydrodynamic focusing for microfluidic impedance cytometry: a system integration study

We present the first in-depth system integration study of in-plane hydrodynamic focusing in a microfluidic impedance cytometry lab-on-a-chip. The method relies on constricting the detection volume with non-conductive sheath flows and characterizing particles or cells based on changes in impedance. This approach represents an avenue of overcoming current limitations in sensitivity with translating cytometers to the point of care for rapid, low-cost blood analysis. While examples of integrated devices are present in the literature, no systematic study of the interplay between hydrodynamics and electrodynamics has been carried out as of yet. We develop analytical and numerical models to describe the impedimetric response of the sensor as a function of cellular characteristics, physical flow properties, and device geometry. We fabricate a working prototype lab-on-a-chip for experimental validation using latex particles. We find that ionic diffusion can be a critical limiting factor even at high Péclet number. Moreover, we explore geometric variations, revealing that the ionic diffusion-related distance between the center of the hydrodynamic focusing junction and the impedance measurement electrodes plays a dominant role. With our device, we demonstrate over fivefold enhancement in impedance signals and population separation with in-plane hydrodynamic focusing. It is only through such in-depth system studies, in both models and experiments, that optimal utilization of microsystem capabilities becomes possible.     

Multimedia information retrieval based on pairwise comparison and its application to visual search

Finding a way to elicit user preferences in the context of multimedia information retrieval is an important issue that remains to be solved. Users are not usually able to find a sought after image or provide an example of what they want. One of several possible methods that might be used to solve this problem involves reasoning about user queries through the assessment of several samples. In this article we propose a method by which user queries are retrieved based on the pairwise comparison of sample alternatives. Pairwise comparison was originally designed for the ranking of alternatives. In our method we rank criteria according to their importance for the user and then use this information to retrieve relevant records from the database. The method was implemented in Matlab and tested on the Microsoft Research Cambridge Image Database.     

Simultaneous measurement of magnetization and magnetostriction in 50 T pulsed high magnetic fields

To simultaneously perform magnetization and magnetostriction measurements in high magnetic fields, a miniaturized device was developed that combines an inductive magnetometer with a capacitive dilatometer and, therefore, it is called "dilamagmeter." This combination of magnetic and magnetoelastic investigations is a new step to a complex understanding of solid state properties. The whole system can be mounted in a 12 mm clear bore of any cryostat usually used in nondestructive pulsed high field magnets. The sensitivity of both methods is about 10(-5) A m(2) for magnetization and 10(-5) relative changes in length for striction measurements. Measurements on a GdSi single crystal, which are corrected by the background signal of the experimental setup, agree well with the results of steady field experiments. All test measurements, which are up until now performed in the temperature range of 4-100 K, confirm the perfect usability and high stability in pulsed fields up to 50 T with a pulse duration of 10 ms.     

Unsupervised natural image patch learning

Computational Visual Media - A metric for natural image patches is an important tool for analyzing images. An efficient means of learning one is to train a deep network to map an image patch to a...     

Automated segmentation of vegetation structure units in a Mediterranean landscape

In Mediterranean regions, the combination of disturbances, life histories, plant regeneration traits, and microhabitat variability form highly heterogeneous vegetation mosaics which shift in space and time. Consequently, structure-based forest management is emerging as a superior alternative to management of vegetation formations in such areas. Delineation of management units in these areas is often based on manual interpretation of aerial imagery coupled with field surveys. Here, we propose an alternative approach that is based on segmentation of remotely sensed height and cover maps derived from light detection and ranging (LiDAR) imagery. A large suite of alternative segmentation maps was generated using multiresolution segmentation (MS) with different parameters, and an area-fit approach used to select the map that most successfully captured a reference set of structural units delineated manually. We assessed the feasibility of this approach in a nature reserve in northern Israel, compared the resulting map with a traditional vegetation formations map, and explored the performance of the segmentation algorithm under various parameter combinations. Pronounced differences between the structure and formation maps highlight the suitability of this approach as an alternative to the existing methods of delineating vegetation units in Mediterranean systems, and possibly in other systems as well.