551 research outputs found

    Gain of a Single Gas Electron Multiplier

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    Gas Electron Multiplier (GEM) is a gaseous detector used in particle detection and is known for its high rate capability. Ever since its invention in 1997, GEM was applied in many areas and recently has been proposed to be installed in the CMS high η regions for upgrade at LHC, CERN. A complete understanding of the working and gain behaviour does not exist. GEM gain is influenced by charging up and this has been variedly interpreted in literature lacking consensus. I have attempted in this work through simulations and measurements to achieve a better understanding of single GEM gain and how it is affected by various factors. Specific experimental methods which evolved with subsequent measurements were employed to systematically study the charging up effect. Information from simulations was applied to characterize measurements thereby enabling the development of a model for charging up. Conductivity mechanism of the dielectric used in GEM was analyzed and the resistivity measured. Gain free of charging up effects was measured and this is appropriate for comparison with simulation

    A dynamic method for charging-up calculations: the case of GEM

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    The simulation of Micro Pattern Gaseous Detectors (MPGDs) signal response is an important and powerful tool for the design and optimization of such detectors. However, several attempts to simulate exactly the effective charge gain have not been completely successful. Namely, the gain stability over time has not been fully understood. Charging-up of the insulator surfaces have been pointed as one of the responsible for the difference between experimental and Monte Carlo results. This work describes two iterative methods to simulate the charging-up in one MPGD device, the Gas Electron Multiplier (GEM). The first method uses a constant step for avalanches time evolution, very detailed, but slower to compute. The second method uses a dynamic step that improves the computing time. Good agreement between both methods was reached. Despite of comparison with experimental results shows that charging-up plays an important role in detectors operation, should not be the only responsible for the difference between simulated and measured effective gain, but explains the time evolution in the effective gain.Comment: Minor changes in grammatical statements and inclusion of some important information about experimental setup at section "Comparison with experimental results

    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

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks