119,858 research outputs found

    A test of arm-induced star formation in spiral galaxies from near-IR and Hα\alpha imaging

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    We have imaged a sample of 20 spiral galaxies in Hα\alpha and in the near-infrared K band (2.2 um), in order to determine the location and strength of star formation in these objects with respect to perturbations in the old stellar population. We have found that star formation rates are significantly enhanced in the vicinity of K band arms. We have also found that this enhancement in star formation rate in arm regions correlates well with a quantity that measures the relative strengths of shocks in arms. Assuming that the K band light is dominated by emission from the old stellar population, this shows that density waves trigger star formation in the vicinity of spiral arms.Comment: 6 pages, 1 figure, accpeted for publication in MNRA

    Sublattice asymmetry of impurity doping in graphene: A review

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    In this review we highlight recent theoretical and experimental work on sublattice asymmetric doping of impurities in graphene, with a focus on substitutional Nitrogen dopants. It is well known that one current limitation of graphene in regards to its use in electronics is that in its ordinary state it exhibits no band gap. By doping one of its two sublattices preferentially it is possible to not only open such a gap, which can furthermore be tuned through control of the dopant concentration, but in theory produce quasi-ballistic transport of electrons in the undoped sublattice, both important qualities for any graphene device to be used competetively in future technology. We outline current experimental techniques for synthesis of such graphene monolayers and detail theoretical efforts to explain the mechanisms responsible for the effect, before suggesting future research directions in this nascent field.Comment: 20 pages, 4 figures. Accepted for publication in Beilstein Journal of Nanotechnolog

    ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data

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    There are many different ways in which change point analysis can be performed, from purely parametric methods to those that are distribution free. The ecp package is designed to perform multiple change point analysis while making as few assumptions as possible. While many other change point methods are applicable only for univariate data, this R package is suitable for both univariate and multivariate observations. Estimation can be based upon either a hierarchical divisive or agglomerative algorithm. Divisive estimation sequentially identifies change points via a bisection algorithm. The agglomerative algorithm estimates change point locations by determining an optimal segmentation. Both approaches are able to detect any type of distributional change within the data. This provides an advantage over many existing change point algorithms which are only able to detect changes within the marginal distributions
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