76 research outputs found

    A model of non-perturbative gluon emission in an initial state parton shower

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    We consider a model of transverse momentum production in which non-perturbative smearing takes place throughout the perturbative evolution, by a simple modification to an initial state parton shower algorithm. Using this as the important non-perturbative ingredient, we get a good fit to data over a wide range of energy. Combining it with the non-perturbative masses and cutoffs that are a feature of conventional parton showers also leads to a reasonable fit. We discuss the extrapolation to the LHC.Comment: 14 pages, 6 figures; version accepted by JHE

    The underlying event and fragmentation

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    A good fit to the CDF underlying event is obtained in the multiple parton scattering picture using HERWIG, after modifying the cluster hadronization algorithm as suggested by our previous study and adopting a larger maximum cluster size. The number of scatters per event is generated simply as a Poisson distribution. If our picture is correct, the baryon yield should be enhanced in the underlying event. This effect may be studied by measuring the proton-to-pion ratio.Comment: 23 pages, 8 figure

    The Underlying Event and the Total Cross Section from Tevatron to the LHC

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    Multiple partonic interactions are widely used to simulate the hadronic final state in high energy hadronic collisions, and successfully describe many features of the data. It is important to make maximum use of the available physical constraints on such models, particularly given the large extrapolation from current high energy data to LHC energies. In eikonal models, the rate of multiparton interactions is coupled to the energy dependence of the total cross section. Using a Monte Carlo implementation of such a model, we study the connection between the total cross section, the jet cross section, and the underlying event. By imposing internal consistency on the model, we derive constraints on its parameters at the LHC. By imposing internal consistency on the model and comparing to current data we constrain the allowed range of its parameters. We show that measurements of the total proton-proton cross-section at the LHC are likely to break this internal consistency, and thus to require an extension of the model. Likely such extensions are that hard scatters probe a denser matter distribution inside the proton in impact parameter space than soft scatters, a conclusion also supported by Tevatron data on double-parton scattering, and/or that the basic parameters of the model are energy dependent.Comment: 17 pages, 6 figures, version accepted by JHE

    Local charge compensation from colour preconfinement as a key to the dynamics of hadronization

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    If, as is commonly accepted, the colour-singlet, `preconfined', perturbative clusters are the primary units of hadronization, then the electric charge is necessarily compensated locally at the scale of the typical cluster mass. As a result, the minijet electric charge is suppressed at scales that are greater than the cluster mass. We hence argue, and demonstrate by means of Monte Carlo simulations using HERWIG, that the scale at which charge compensation is violated is close to the mass of the clusters involved in hadronization, and its measurement would provide a clue to resolving the nature of the dynamics. We repeat the calculation using PYTHIA and find that the numbers produced by the two generators are similar. The cluster mass distribution is sensitive to soft emission that is considered unresolved in the parton shower phase. We discuss how the description of the splitting of large clusters in terms of unresolved emission modifies the algorithm of HERWIG, and relate the findings to the yet unknown underlying nonperturbative mechanism. In particular, we propose a form of αS\alpha_S that follows from a power-enhanced beta function, and discuss how this αS\alpha_S that governs unresolved emission may be related to power corrections. Our findings are in agreement with experimental data.Comment: 37 pages, 20 figure

    The landscape of viral associations in human cancers

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    Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, for which whole-genome and—for a subset—whole-transcriptome sequencing data from 2,658 cancers across 38 tumor types was aggregated, we systematically investigated potential viral pathogens using a consensus approach that integrated three independent pipelines. Viruses were detected in 382 genome and 68 transcriptome datasets. We found a high prevalence of known tumor-associated viruses such as Epstein–Barr virus (EBV), hepatitis B virus (HBV) and human papilloma virus (HPV; for example, HPV16 or HPV18). The study revealed significant exclusivity of HPV and driver mutations in head-and-neck cancer and the association of HPV with APOBEC mutational signatures, which suggests that impaired antiviral defense is a driving force in cervical, bladder and head-and-neck carcinoma. For HBV, HPV16, HPV18 and adeno-associated virus-2 (AAV2), viral integration was associated with local variations in genomic copy numbers. Integrations at the TERT promoter were associated with high telomerase expression evidently activating this tumor-driving process. High levels of endogenous retrovirus (ERV1) expression were linked to a worse survival outcome in patients with kidney cancer

    Colour reconnections in Herwig++

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    We describe the implementation details of the colour reconnection model in the event generator Herwig++. We study the impact on final-state observables in detail and confirm the model idea from colour preconfinement on the basis of studies within the cluster hadronization model. Moreover, we show that the description of minimum bias and underlying event data at the LHC is improved with this model and present results of a tune to available data.Comment: 19 pages, 21 figures, 2 tables. Matches with published versio

    A statistical framework for integrating two microarray data sets in differential expression analysis

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    <p>Abstract</p> <p>Background</p> <p>Different microarray data sets can be collected for studying the same or similar diseases. We expect to achieve a more efficient analysis of differential expression if an efficient statistical method can be developed for integrating different microarray data sets. Although many statistical methods have been proposed for data integration, the genome-wide concordance of different data sets has not been well considered in the analysis.</p> <p>Results</p> <p>Before considering data integration, it is necessary to evaluate the genome-wide concordance so that misleading results can be avoided. Based on the test results, different subsequent actions are suggested. The evaluation of genome-wide concordance and the data integration can be achieved based on the normal distribution based mixture models.</p> <p>Conclusion</p> <p>The results from our simulation study suggest that misleading results can be generated if the genome-wide concordance issue is not appropriately considered. Our method provides a rigorous parametric solution. The results also show that our method is robust to certain model misspecification and is practically useful for the integrative analysis of differential expression.</p
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