1,468 research outputs found

    Stellar Populations and Star Cluster Formation in Interacting Galaxies with the Advanced Camera for Surveys

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    Pixel-by-pixel colour-magnitude and colour-colour diagrams - based on a subset of the Hubble Space Telescope Advanced Camera for Surveys Early Release Observations - provide a powerful technique to explore and deduce the star and star cluster formation histories of the Mice and the Tadpole interacting galaxies. In each interacting system we find some 40 bright young star clusters (20 <= F606W (mag) <= 25, with a characteristic mass of ~3 x 10^6 Msun), which are spatially coincident with blue regions of active star formation in their tidal tails and spiral arms. We estimate that the main events triggering the formation of these clusters occurred ~(1.5-2.0) x 10^8 yr ago. We show that star cluster formation is a major mode of star formation in galaxy interactions, with >= 35% of the active star formation in encounters occurring in star clusters. This is the first time that young star clusters have been detected along the tidal tails in interacting galaxies. The tidal tail of the Tadpole system is dominated by blue star forming regions, which occupy some 60% of the total area covered by the tail and contribute ~70% of the total flux in the F475W filter (decreasing to ~40% in F814W). The remaining pixels in the tail have colours consistent with those of the main disk. The tidally triggered burst of star formation in the Mice is of similar strength in both interacting galaxies, but it has affected only relatively small, spatially coherent areas.Comment: 23 pages in preprint form, 6 (encapsulated) postscript figures; accepted for publication in New Astronomy; ALL figures (even the grey-scale ones) need to be printed on a colour printer style files included; for full-resolution paper, see http://www.ast.cam.ac.uk/STELLARPOPS/ACSpaper

    Measurement of differential cross sections for top quark pair production using the lepton plus jets final state in proton-proton collisions at 13 TeV

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    National Science Foundation (U.S.

    Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

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    Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated tt‾\mathrm{t}\overline{\mathrm{t}} events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV)

    Particle-flow reconstruction and global event description with the CMS detector

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    The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic tau decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8 TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions

    Search for heavy resonances decaying to a top quark and a bottom quark in the lepton+jets final state in proton–proton collisions at 13 TeV

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    info:eu-repo/semantics/publishe

    Evidence for the Higgs boson decay to a bottom quark–antiquark pair

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    info:eu-repo/semantics/publishe

    Pseudorapidity and transverse momentum dependence of flow harmonics in pPb and PbPb collisions

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    info:eu-repo/semantics/publishe

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon