Coulomb scattering with remote continuum states in quantum dot devices

Electron capture and emission by Coulomb scattering in self-assembled quantum dot (QD) devices is studied theoretically. While the dependence of the Coulomb scattering (Auger) rates on the local wetting layer electron density has been a topic of intense research, we put special interest on the remote scattering between QD electrons and continuum electrons originating from a quantum well, doped bulk layers or metal contacts. Numerical effort is made to include all microscopic transitions between the Fermi distributed continuum states. The remote Coulomb scattering is investigated as a function of the electron density, the distance from the QDs and the temperature. Our results are compared with experimental observations, considering lifetime limitations in QD memory structures as well as the electron emission in pn-diodes

Distance-generalized Core Decomposition

The $k$-core of a graph is defined as the maximal subgraph in which every vertex is connected to at least $k$ other vertices within that subgraph. In this work we introduce a distance-based generalization of the notion of $k$-core, which we refer to as the $(k,h)$-core, i.e., the maximal subgraph in which every vertex has at least $k$ other vertices at distance $\leq h$ within that subgraph. We study the properties of the $(k,h)$-core showing that it preserves many of the nice features of the classic core decomposition (e.g., its connection with the notion of distance-generalized chromatic number) and it preserves its usefulness to speed-up or approximate distance-generalized notions of dense structures, such as $h$-club. Computing the distance-generalized core decomposition over large networks is intrinsically complex. However, by exploiting clever upper and lower bounds we can partition the computation in a set of totally independent subcomputations, opening the door to top-down exploration and to multithreading, and thus achieving an efficient algorithm

Current Distribution and random matrix ensembles for an integrable asymmetric fragmentation process

We calculate the time-evolution of a discrete-time fragmentation process in which clusters of particles break up and reassemble and move stochastically with size-dependent rates. In the continuous-time limit the process turns into the totally asymmetric simple exclusion process (only pieces of size 1 break off a given cluster). We express the exact solution of master equation for the process in terms of a determinant which can be derived using the Bethe ansatz. From this determinant we compute the distribution of the current across an arbitrary bond which after appropriate scaling is given by the distribution of the largest eigenvalue of the Gaussian unitary ensemble of random matrices. This result confirms universality of the scaling form of the current distribution in the KPZ universality class and suggests that there is a link between integrable particle systems and random matrix ensembles.Comment: 11 page

Seasonal and interannual variability of cladoceran communities in two peri-alpine lakes: uncoupled response to the 2003 heat wave

Seasonal and interannual dynamics of cladoceran species were analyzed during the period 1995–2003 in two deep peri-alpine lakes morphologically different but subjected to similar regional climatic forcing. The seasonal succession of cladoceran species was characterized and the impact of extreme climatic events on the annual pattern of species succession was assessed. Using a multivariate method, we show that the cladoceran species display marked seasonality patterns that differed in the two lakes. The differences observed between the lakes were driven by their trophic state, the plankton species composition and the abundance of predators. We show that the sensitivity of the annual pattern of species succession to extreme weather changes, illustrated by the 2003 heat wave, differs markedly in these two lakes. In Lake Annecy, the annual pattern of cladoceran succession observed in 2003 is not different from the one usually observed. In contrast, in Lake Geneva, the annual pattern recorded in 2003 is unusual and characterized by the maintenance of herbivorous cladocera during summer. These findings underline the need to consider the morphology of lakes and trophic state in the assessment of ecological responses to global warming. Our results contribute to the debate about the predictability of the impacts of climate change on aquatic ecosystems, and their extrapolation from one site to another

Sustainable farming with native rocks: the transition without revolution.

The development process which humanity passed through favored a series of conquests, reflected in the better quality of life and longevity, however, it also provoked upsets and severe transformation in the environment and in the human food security. Such process is driving the ecosystems to be homogeneous, and, therefore,the nutrients� supply, via nourishment. To change this panorama, the present work discusses the gains of incorporating the stonemeal technique as a strategic alternative to give back the essential fertile characteristics to the soils. This technology has the function of facilitating the rejuvenation of the soils and increasing the availability of the necessary nutrients to the full development of the plants which is a basic input for the proliferation of life in all its dimensions

Noise in laser speckle correlation and imaging techniques

We study the noise of the intensity variance and of the intensity correlation and structure functions measured in light scattering from a random medium in the case when these quantities are obtained by averaging over a finite number N of pixels of a digital camera. We show that the noise scales as 1/N in all cases and that it is sensitive to correlations of signals corresponding to adjacent pixels as well as to the effective time averaging (due to the finite sampling time) and spatial averaging (due to the finite pixel size). Our results provide a guide to estimation of noise level in such applications as the multi-speckle dynamic light scattering, time-resolved correlation spectroscopy, speckle visibility spectroscopy, laser speckle imaging etc.Comment: submitted 14 May 201

Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we present a new machine-learning method, critical random networks (CRNs), for predicting one-dimensional structures, and apply it, with position-specific scoring matrices, to the prediction of secondary structures (SS), contact numbers (CN), and residue-wise contact orders (RWCO). The present method achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS prediction is comparable to other state-of-the-art methods, and that of the CN prediction is a significant improvement over previous methods. We give a detailed formulation of critical random networks-based prediction scheme, and examine the context-dependence of prediction accuracies. In order to study the nonlinear and multi-body effects, we compare the CRNs-based method with a purely linear method based on position-specific scoring matrices. Although not superior to the CRNs-based method, the surprisingly good accuracy achieved by the linear method highlights the difficulty in extracting structural features of higher order from amino acid sequence beyond that provided by the position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for publication in BIOPHYSIC