Optical Excitations and Field Enhancement in Short Graphene Nanoribbons

The optical excitations of elongated graphene nanoflakes of finite length are investigated theoretically through quantum chemistry semiempirical approaches. The spectra and the resulting dipole fields are analyzed, accounting in full atomistic details for quantum confinement effects, which are crucial in the nanoscale regime. We find that the optical spectra of these nanostructures are dominated at low energy by excitations with strong intensity, comprised of characteristic coherent combinations of a few single-particle transitions with comparable weight. They give rise to stationary collective oscillations of the photoexcited carrier density extending throughout the flake and to a strong dipole and field enhancement. This behavior is robust with respect to width and length variations, thus ensuring tunability in a large frequency range. The implications for nanoantennas and other nanoplasmonic applications are discussed for realistic geometries.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Magnetic excitations in the spin-1 anisotropic antiferromagnet NiCl2-4SC(NH2)(2)

The spin-1 anisotropic antiferromagnet NiCl2-4SC(NH2)(2) exhibits a field-induced quantum phase transition that is formally analogous to Bose-Einstein condensation. Here we present results of systematic high-field electron spin resonance (ESR) experimental and theoretical studies of this compound with a special emphasis on single-ion two-magnon bound states. In order to clarify some remaining discrepancies between theory and experiment, the frequency-field dependence of magnetic excitations in this material is reanalyzed. In particular, a more comprehensive interpretation of the experimental signature of single-ion two-magnon bound states is shown to be fully consistent with theoretical results. We also clarify the structure of the ESR spectrum in the so-called intermediate phase.

Reproducing kernel Hilbert spaces associated with kernels on topological spaces

We analyze reproducing kernel Hilbert spaces of positive definite kernels on a topological space X being either first countable or locally compact. The results include versions of Mercer's theorem and theorems on the embedding of these spaces into spaces of continuous and square integrable functions.

QUASI-TOPOLOGICAL QUANTUM FIELD THEORIES AND Z(2) LATTICE GAUGE THEORIES

We consider a two-parameter family of Z(2) gauge theories on a lattice discretization T(M) of a three-manifold M and its relation to topological field theories. Familiar models such as the spin-gauge model are curves on a parameter space Gamma. We show that there is a region Gamma(0) subset of Gamma where the partition function and the expectation value h < W-R(gamma)> i of the Wilson loop can be exactly computed. Depending on the point of Gamma(0), the model behaves as topological or quasi-topological. The partition function is, up to a scaling factor, a topological number of M. The Wilson loop on the other hand, does not depend on the topology of gamma. However, for a subset of Gamma(0), < W-R(gamma)> depends on the size of gamma and follows a discrete version of an area law. At the zero temperature limit, the spin-gauge model approaches the topological and the quasi-topological regions depending on the sign of the coupling constant.

Predicting the connectivity of primate cortical networks from topological and spatial node properties

Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.

Spatial reference of black capuchin monkeys in Brazilian Atlantic Forest: egocentric or allocentric?

Wild primates occupy large home ranges and travel long distances to reach goals. However, how primates are able to remember goal locations and travel efficiently is unclear. Few studies present consistent results regarding what reference system primates use to navigate, and what kind of spatial information they recognize. We analysed the pattern of navigation of one wild group of black capuchin monkeys, Cebus nigritus, at Atlantic Forest for 100 days in Carlos Botelho State Park (PECB), Brazil. We tested predictions based on the alternative hypotheses that black capuchin monkeys navigate using a sequence of landmarks as an egocentric reference system or an allocentric reference system, or both, depending on availability of food resources. The group location was recorded using a GPS device collecting coordinates at 5 min intervals, and route maps were generated using ArcView v9.3.1. The study group travelled through habitual routes during less than 30% of our study sample, and revisited resources from different starting points, using different paths and routes, even when prominent landmarks near feeding locations were not visible. The study group used habitual routes more frequently when high-quality foods were scarce, and navigated using different paths when revisiting food sources. Results support the hypothesis that black capuchin monkeys at PECB navigate using both egocentric and allocentric systems of reference, depending on the quality and distribution of the food resource they find. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Topology Verification for Isosurface Extraction

The broad goals of verifiable visualization rely on correct algorithmic implementations. We extend a framework for verification of isosurfacing implementations to check topological properties. Specifically, we use stratified Morse theory and digital topology to design algorithms which verify topological invariants. Our extended framework reveals unexpected behavior and coding mistakes in popular publicly available isosurface codes.

Lindelof spaces which are indestructible, productive, or D

We discuss relationships in Lindelof spaces among the properties "indestructible". "productive", "D", and related properties. (C) 2011 Elsevier B.V. All rights reserved.

Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Dynamics of doublon-holon pairs in Hubbard two-leg ladders

The dynamics of holon-doublon pairs is studied in Hubbard two-leg ladders using the time-dependent density matrix renormalization group method. We find that the geometry of the two-leg ladder, which is qualitatively different from a one-dimensional chain due to the presence of a spin gap, strongly affects the propagation of a doublon-holon pair. Two distinct regimes are identified. For weak interleg coupling, the results are qualitatively similar to the case of the propagation previously reported in Hubbard chains, with only a renormalization of parameters. More interesting is the case of strong interleg coupling where substantial differences arise, particularly regarding the double occupancy and properties of the excitations such as the doublon speed. Our results suggest a connection between the presence of a spin gap and qualitative changes in the doublon speed, indicating a weak coupling between the doublon and the magnetic excitations.

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

A simple criterion to predict the glass forming ability of metallic alloys

A new and simple criterion with which to quantitatively predict the glass forming ability (GFA) of metallic alloys is proposed. It was found that the critical cooling rate for glass formation (R-C) correlates well with a proper combination of two factors, the minimum topological instability (lambda(min)) and the Delta h parameter, which depends on the average work function difference (Delta phi) and the average electron density difference (Delta n(ws)(1/3)) among the constituent elements of the alloy. A correlation coefficient (R-2) of 0.76 was found between R-c and the new criterion for 68 alloys in 30 different metallic systems. The new criterion and the Uhlmann's approach were used to estimate the critical amorphous thickness (Z(C)) of alloys in the Cu-Zr system. The new criterion underestimated R-C in the Cu-Zr system, producing predicted Z(C) values larger than those observed experimentally. However, when considering a scale factor, a remarkable similarity was observed between the predicted and the experimental behavior of the GFA in the binary Cu-Zr. When using the same scale factor and performing the calculation for the ternary Zr-Cu-Al, good agreement was found between the predicted and the actual best GFA region, as well as between the expected and the observed critical amorphous thickness. (C) 2012 American Institute of Physics. [doi:10.1063/1.3676196]