Effects of gluon number fluctuations on photon - photon collisions at high energies

We investigate the effects of gluon number fluctuations on the total $\gamma\gamma$, $\gamma^*\gamma^*$ cross sections and the photon structure function $F_2^\gamma(x,Q^2)$. Considering a model which relates the dipole-dipole and dipole-hadron scattering amplitudes, we estimate these observables by using event-by-event and physical amplitudes. We demonstrate that both analyses are able to describe the LEP data, but predict different behaviours for the observables at high energies, with the gluon fluctuations effects decreasing the cross sections. We conclude that the study of $\gamma \gamma$ interactions can be useful to constrain the QCD dynamics.Comment: 9 pages, 6 figures. Improved version with two new figures. Version to be published in Physical Review

γ∗p\gamma^*p cross section from the dipole model in momentum space

We reproduce the DIS measurements of the proton structure function at high energy from the dipole model in momentum space. To model the dipole-proton forward scattering amplitude, we use the knowledge of asymptotic solutions of the Balitsky-Kovchegov equation, describing high-energy QCD in the presence of saturation effects. We compare our results with the previous analysis in coordinate space and discuss possible extensions of our approach.Comment: 9 pages, 3 figure

Modelagem do crescimento de culturas: aplicações à cultura do milho.

Características gerais dos modelos de culturas; Principais modelos de culturas; Possibilidades de aplicação dos modelos de cultura; Aplicação no manejo da cultura; Aplicação na análise da resposta de culturas à irrigação e no planejamento do uso de recursos hídricos; Aplicação no manejo de nitrogênio; Aplicação na avalização de risco climático e no prognóstico de safras; Aplicação na análise da sustentabilidade de sistemas de sucessão de culturas; Aplicação em estudos de variabilidade espacial e em manejo sítio-específico; Aplicação no planejamento de uso da terra e dos recursos naturais; Aplicação na genética e melhoramento e na análise da interação genótipo x ambiente; Aplicação na simulação do efeito de pragas, doenças e plantas daninhas; Aplicação nos estudos de mudanças climáticas; Aplicação como ferramenta de educação e transferência de tecnologia; Limitações dos modelos de crescimento de culturas; Potencialidades de aplicação de modelos de simulação de culturas no Brasil.bitstream/CNPMS-2010/22537/1/Doc-91.pd

DIS and the effects of fluctuations: a momentum space analysis

Among the dipole models of deep inelastic scattering at small values of the Bjorken variable $x$, one has been recently proposed which relates the virtual photon-proton cross section to the dipole-proton forward scattering amplitude in momentum space. The latter is parametrized by an expression which interpolates between its behavior at saturation and the travelling wave, ultraviolet, amplitudes predicted by perturbative QCD from the Balitsky-Kovchegov equation. Inspired by recent developments in coordinate space, we use this model to parametrize the proton structure function and confront it to HERA data on $ep$ deep inelastic scattering. Both event-by-event and the physical amplitudes are considered, the latter used to investigate the effect of gluon number fluctuations, beyond the mean-field approximation. We conclude that fluctuations are not present in DIS at HERA energies.Comment: 9 pages, 2 figure

QCD at small x and nucleus-nucleus collisions

At large collision energy sqrt(s) and relatively low momentum transfer Q, one expects a new regime of Quantum Chromo-Dynamics (QCD) known as "saturation". This kinematical range is characterized by a very large occupation number for gluons inside hadrons and nuclei; this is the region where higher twist contributions are as large as the leading twist contributions incorporated in collinear factorization. In this talk, I discuss the onset of and dynamics in the saturation regime, some of its experimental signatures, and its implications for the early stages of Heavy Ion Collisions.Comment: Plenary talk given at QM2006, Shanghai, November 2006. 8 pages, 8 figure

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis