Pathwise convergence of the Euler scheme for rough and stochastic differential equations

The convergence of the first order Euler scheme and an approximative variant thereof, along with convergence rates, are established for rough differential equations driven by c\`adl\`ag paths satisfying a suitable criterion, namely the so-called Property (RIE), along time discretizations with vanishing mesh size. This property is then verified for almost all sample paths of Brownian motion, It\^o processes, L\'evy processes and general c\`adl\`ag semimartingales, as well as the driving signals of both mixed and rough stochastic differential equations, relative to various time discretizations. Consequently, we obtain pathwise convergence in p-variation of the Euler--Maruyama scheme for stochastic differential equations driven by these processes.Comment: 43 page

Observed and simulated precipitation responses in wet and dry regions 1850–2100

Global warming is expected to enhance fluxes of fresh water between the surface and atmosphere, causing wet regions to become wetter and dry regions drier, with serious implications for water resource management. Defining the wet and dry regions as the upper 30% and lower 70% of the precipitation totals across the tropics (30° S–30° N) each month we combine observations and climate model simulations to understand changes in the wet and dry regions over the period 1850–2100. Observed decreases in precipitation over dry tropical land (1950–2010) are also simulated by coupled atmosphere–ocean climate models (−0.3%/decade) with trends projected to continue into the 21st century. Discrepancies between observations and simulations over wet land regions since 1950 exist, relating to decadal fluctuations in El Niño southern oscillation, the timing of which is not represented by the coupled simulations. When atmosphere-only simulations are instead driven by observed sea surface temperature they are able to adequately represent this variability over land. Global distributions of precipitation trends are dominated by spatial changes in atmospheric circulation. However, the tendency for already wet regions to become wetter (precipitation increases with warming by 3% K−1 over wet tropical oceans) and the driest regions drier (precipitation decreases of −2% K−1 over dry tropical land regions) emerges over the 21st century in response to the substantial surface warming

Document Filtering for Long-tail Entities

Filtering relevant documents with respect to entities is an essential task in the context of knowledge base construction and maintenance. It entails processing a time-ordered stream of documents that might be relevant to an entity in order to select only those that contain vital information. State-of-the-art approaches to document filtering for popular entities are entity-dependent: they rely on and are also trained on the specifics of differentiating features for each specific entity. Moreover, these approaches tend to use so-called extrinsic information such as Wikipedia page views and related entities which is typically only available only for popular head entities. Entity-dependent approaches based on such signals are therefore ill-suited as filtering methods for long-tail entities. In this paper we propose a document filtering method for long-tail entities that is entity-independent and thus also generalizes to unseen or rarely seen entities. It is based on intrinsic features, i.e., features that are derived from the documents in which the entities are mentioned. We propose a set of features that capture informativeness, entity-saliency, and timeliness. In particular, we introduce features based on entity aspect similarities, relation patterns, and temporal expressions and combine these with standard features for document filtering. Experiments following the TREC KBA 2014 setup on a publicly available dataset show that our model is able to improve the filtering performance for long-tail entities over several baselines. Results of applying the model to unseen entities are promising, indicating that the model is able to learn the general characteristics of a vital document. The overall performance across all entities---i.e., not just long-tail entities---improves upon the state-of-the-art without depending on any entity-specific training data.Comment: CIKM2016, Proceedings of the 25th ACM International Conference on Information and Knowledge Management. 201

Highly controlled, reproducible measurements of aerosol emissions from combustion of a common African biofuel source

Particulate emissions from biomass burning can both alter the atmosphere's radiative balance and cause significant harm to human health. However, due to the large effect on emissions caused by even small alterations to the way in which a fuel burns, it is difficult to study particulate production of biomass combustion mechanistically and in a repeatable manner. In order to address this gap, in this study, small wood samples sourced from Côte D'Ivoire in West Africa were burned in a highly controlled laboratory environment. The shape and mass of samples, available airflow and surrounding thermal environment were carefully regulated. Organic aerosol and refractory black carbon emissions were measured in real time using an Aerosol Mass Spectrometer and a Single Particle Soot Photometer, respectively. This methodology produced remarkably repeatable results, allowing aerosol emissions to be mapped directly onto different phases of combustion. Emissions from pyrolysis were visible as a distinct phase before flaming was established. After flaming combustion was initiated, a black-carbon-dominant flame was observed during which very little organic aerosol was produced, followed by a period that was dominated by organic-carbon-producing smouldering combustion, despite the presence of residual flaming. During pyrolysis and smouldering, the two phases producing organic aerosol, distinct mass spectral signatures that correspond to previously reported variations in biofuel emissions measured in the atmosphere are found. Organic aerosol emission factors averaged over an entire combustion event were found to be representative of the time spent in the pyrolysis and smouldering phases, rather than reflecting a coupling between emissions and the mass loss of the sample. Further exploration of aerosol yields from similarly carefully controlled fires and a careful comparison with data from macroscopic fires and real-world emissions will help to deliver greater constraints on the variability of particulate emissions in atmospheric systems

Tight-binding study of the influence of the strain on the electronic properties of InAs/GaAs quantum dots

We present an atomistic investigation of the influence of strain on the electronic properties of quantum dots (QD's) within the empirical $s p^{3} s^{*}$ tight-binding (ETB) model with interactions up to 2nd nearest neighbors and spin-orbit coupling. Results for the model system of capped pyramid-shaped InAs QD's in GaAs, with supercells containing $10^{5}$ atoms are presented and compared with previous empirical pseudopotential results. The good agreement shows that ETB is a reliable alternative for an atomistic treatment. The strain is incorporated through the atomistic valence force field model. The ETB treatment allows for the effects of bond length and bond angle deviations from the ideal InAs and GaAs zincblende structure to be selectively removed from the electronic-structure calculation, giving quantitative information on the importance of strain effects on the bound state energies and on the physical origin of the spatial elongation of the wave functions. Effects of dot-dot coupling have also been examined to determine the relative weight of both strain field and wave function overlap.Comment: 22 pages, 7 figures, submitted to Phys. Rev. B (in press) In the latest version, added Figs. 3 and 4, modified Fig. 5, Tables I and II,.and added new reference

Mapping the unconventional orbital texture in topological crystalline insulators

The newly discovered topological crystalline insulators (TCIs) harbor a complex band structure involving multiple Dirac cones. These materials are potentially highly tunable by external electric field, temperature or strain and could find future applications in field-effect transistors, photodetectors, and nano-mechanical systems. Theoretically, it has been predicted that different Dirac cones, offset in energy and momentum-space, might harbor vastly different orbital character, a unique property which if experimentally realized, would present an ideal platform for accomplishing new spintronic devices. However, the orbital texture of the Dirac cones, which is of immense importance in determining a variety of materials properties, still remains elusive in TCIs. Here, we unveil the orbital texture in a prototypical TCI Pb$_{1-x}$Sn$_x$Se. By using Fourier-transform (FT) scanning tunneling spectroscopy (STS) we measure the interference patterns produced by the scattering of surface state electrons. We discover that the intensity and energy dependences of FTs show distinct characteristics, which can directly be attributed to orbital effects. Our experiments reveal the complex band topology involving two Lifshitz transitions and establish the orbital nature of the Dirac bands in this new class of topological materials, which could provide a different pathway towards future quantum applications

Strongly Correlated Quantum Fluids: Ultracold Quantum Gases, Quantum Chromodynamic Plasmas, and Holographic Duality

Strongly correlated quantum fluids are phases of matter that are intrinsically quantum mechanical, and that do not have a simple description in terms of weakly interacting quasi-particles. Two systems that have recently attracted a great deal of interest are the quark-gluon plasma, a plasma of strongly interacting quarks and gluons produced in relativistic heavy ion collisions, and ultracold atomic Fermi gases, very dilute clouds of atomic gases confined in optical or magnetic traps. These systems differ by more than 20 orders of magnitude in temperature, but they were shown to exhibit very similar hydrodynamic flow. In particular, both fluids exhibit a robustly low shear viscosity to entropy density ratio which is characteristic of quantum fluids described by holographic duality, a mapping from strongly correlated quantum field theories to weakly curved higher dimensional classical gravity. This review explores the connection between these fields, and it also serves as an introduction to the Focus Issue of New Journal of Physics on Strongly Correlated Quantum Fluids: from Ultracold Quantum Gases to QCD Plasmas. The presentation is made accessible to the general physics reader and includes discussions of the latest research developments in all three areas.Comment: 138 pages, 25 figures, review associated with New Journal of Physics special issue "Focus on Strongly Correlated Quantum Fluids: from Ultracold Quantum Gases to QCD Plasmas" (http://iopscience.iop.org/1367-2630/focus/Focus%20on%20Strongly%20Correlated%20Quantum%20Fluids%20-%20from%20Ultracold%20Quantum%20Gases%20to%20QCD%20Plasmas

Spectroscopic scanning tunneling microscopy insights into Fe-based superconductors

In the first three years since the discovery of Fe-based high Tc superconductors, scanning tunneling microscopy (STM) and spectroscopy have shed light on three important questions. First, STM has demonstrated the complexity of the pairing symmetry in Fe-based materials. Phase-sensitive quasiparticle interference (QPI) imaging and low temperature spectroscopy have shown that the pairing order parameter varies from nodal to nodeless s\pm within a single family, FeTe1-xSex. Second, STM has imaged C4 -> C2 symmetry breaking in the electronic states of both parent and superconducting materials. As a local probe, STM is in a strong position to understand the interactions between these broken symmetry states and superconductivity. Finally, STM has been used to image the vortex state, giving insights into the technical problem of vortex pinning, and the fundamental problem of the competing states introduced when superconductivity is locally quenched by a magnetic field. Here we give a pedagogical introduction to STM and QPI imaging, discuss the specific challenges associated with extracting bulk properties from the study of surfaces, and report on progress made in understanding Fe-based superconductors using STM techniques.Comment: 36 pages, 23 figures, 229 reference

Castor bean organelle genome sequencing and worldwide genetic diversity analysis

Castor bean is an important oil-producing plant in the Euphorbiaceae family. Its high-quality oil contains up to 90% of the unusual fatty acid ricinoleate, which has many industrial and medical applications. Castor bean seeds also contain ricin, a highly toxic Type 2 ribosome-inactivating protein, which has gained relevance in recent years due to biosafety concerns. In order to gain knowledge on global genetic diversity in castor bean and to ultimately help the development of breeding and forensic tools, we carried out an extensive chloroplast sequence diversity analysis. Taking advantage of the recently published genome sequence of castor bean, we assembled the chloroplast and mitochondrion genomes extracting selected reads from the available whole genome shotgun reads. Using the chloroplast reference genome we used the methylation filtration technique to readily obtain draft genome sequences of 7 geographically and genetically diverse castor bean accessions. These sequence data were used to identify single nucleotide polymorphism markers and phylogenetic analysis resulted in the identification of two major clades that were not apparent in previous population genetic studies using genetic markers derived from nuclear DNA. Two distinct sub-clades could be defined within each major clade and large-scale genotyping of castor bean populations worldwide confirmed previously observed low levels of genetic diversity and showed a broad geographic distribution of each sub-clade