Isospin breaking effects in the X(3872) resonance

In this paper we study the effects of isospin breaking in the dynamical generation of the X(3872) state. We also calculate the ratio of the branching fractions of the $X$ decaying into $J/\psi$ with two and three pions, which has been measured experimentally to be close to unity. Together with the X(3872), of positive C-parity, we predict the existence of a negative C-parity state and we comment on which decay channel is more promising to observe this state.Comment: 10 pages, 6 figures, study on the line shape of the X(3872) adde

Charm and Hidden Charm Scalar Resonances in Nuclear Matter

We study the properties of the scalar charm resonances $D_{s0}(2317)$ and $D_0(2400)$, and the theoretical hidden charm state X(3700) in nuclear matter. We find that for the $D_{s0}(2317)$ and X(3700) resonances, with negligible and small width at zero density, respectively, the width becomes about $100 {\rm MeV}$ and $200 {\rm MeV}$ at normal nuclear matter density, accordingly. For $D_0(2400)$ the change in width is relatively less important. We discuss the origin of this new width and trace it to reactions occurring in the nucleus. We also propose a possible experimental test for those modifications in nuclear matter, which will bring valuable information on the nature of those scalar resonances and the interaction of $D$ mesons with nucleons.Comment: 3 pages, 3 figures, to appear in the proceedings of the International Conference on Particles And Nuclei (PANIC08), Eilat, Israel, November 9-14, 200

An algorithm for network community structure determination by surprise

Graphs representing real world systems may be studied from their underlying community structure. A community in a network is an intuitive idea for which there is no consensus on its objective mathematical definition. The most used metric in order to detect communities is the modularity, though many disadvantages of this parameter have already been noticed in the literature. In this work, we present a new approach based on a different metric: the surprise. Moreover, the biases of different community detection algorithms and benchmark networks are thoroughly studied, identified and commented about.Comment: 29 pages, 6 figures, 7 table

To Google or not : differences on how online searches predict names and faces

Word and face recognition are processes of interest for a large number of fields, including both clinical psychology and computer calculations. The research examined here aims to evaluate the role of an online frequency’s ability to predict both face and word recognition by examining the stability of these processes in a given amount of time. The study will further examine the differences between traditional theories and current contextual frequency approaches. Reaction times were recorded through both a logarithmic transformation and through a Bayesian approach. The Bayes factor notation was employed as an additional test to support the evidence provided by the data. Although differences between face and name recognition were found, the results suggest that latencies for both face and name recognition are stable for a period of six months and online news frequencies better predict reaction time for both classical frequentist analyses. These findings support the use of the contextual diversity approach

The small-world of 'Le Petit Prince': Revisiting the word frequency distribution

[EN] Many complex systems are naturally described through graph theory, and different kinds of systems described as networks present certain important characteristics in common. One of these features is the so-called scale-free distribution for its node s connectivity, which means that the degree distribution for the network s nodes follows a power law. Scale-free networks are usually referred to as small-world because the average distance between their nodes do not scale linearly with the size of the network, but logarithmically. Here we present a mathematical analysis on linguistics: the word frequency effect for different translations of the Le Petit Prince in different languages. Comparison of word association networks with random networks makes evident the discrepancy between the random Erdo¿s-Re¿ny model for graphs and real-world networks.Gamermann ., D.; Moret-Tatay, C.; Navarro Pardo, E.; Fernández De Córdoba, P. (2016). The small-world of 'Le Petit Prince': Revisiting the word frequency distribution. Digital Scholarship in the Humanities. 32(2):301-311. doi:10.1093/llc/fqw005S30131132

Large scale evaluation of differences between network-based and pairwise sequence-alignment-based methods of dendrogram reconstruction

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