273 research outputs found

    Studying top quark decay into the polarized W-boson in the TC2 model

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    We study the decay mode of top quark decaying into Wb in the TC2 model where the top quark is distinguished from other fermions by participating in a strong interaction. We find that the TC2 correction to the decay width Γ(t→bW)\Gamma (t \to b W) is generally several percent and maximum value can reach 8% for the currently allowed parameters. The magnitude of such correction is comparable with QCD correction and larger than that of minimal supersymmetric model. Such correction might be observable in the future colliders. We also study the TC2 correction to the branching ratio of top quark decay into the polarized W bosons and find the correction is below 1 1 % . After considering the TC2 correction, we find that our theoretical predictions about the decay branching ratio are also consistent with the experimental data.Comment: 8 pages, 4 figure

    A Reference-Free Algorithm for Computational Normalization of Shotgun Sequencing Data

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    Deep shotgun sequencing and analysis of genomes, transcriptomes, amplified single-cell genomes, and metagenomes has enabled investigation of a wide range of organisms and ecosystems. However, sampling variation in short-read data sets and high sequencing error rates of modern sequencers present many new computational challenges in data interpretation. These challenges have led to the development of new classes of mapping tools and {\em de novo} assemblers. These algorithms are challenged by the continued improvement in sequencing throughput. We here describe digital normalization, a single-pass computational algorithm that systematizes coverage in shotgun sequencing data sets, thereby decreasing sampling variation, discarding redundant data, and removing the majority of errors. Digital normalization substantially reduces the size of shotgun data sets and decreases the memory and time requirements for {\em de novo} sequence assembly, all without significantly impacting content of the generated contigs. We apply digital normalization to the assembly of microbial genomic data, amplified single-cell genomic data, and transcriptomic data. Our implementation is freely available for use and modification
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