1,165 research outputs found

    A new dipole-based jet clustering algorithm

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    Jet production occurs very often in particle physics experiments, and a very good understanding of how partons evolve into jets has been achieved over the last 30 years. The main tool in jet analysis is jet clustering algorithms, and because the problem of clustering particles back to initial partons can not be solved exactly, many different algorithms have been developed. In this work, we propose a new dipole-based jet clustering algorithm, called the dipole-ktk_t algorithm with two main features; it uses a Lorentz invariant distance measure, and it does 3 to 2 recombinations in an attempt to "invert" a dipole-based parton shower. We validate its exclusive version by comparing it to the k_t-algorithm. We then proceed to analyze the dipole-k_t results in W-production events in proton proton collisions, where the has a large transverse momentum and decays into jets. A simple analysis of the W mass reconstruction strengthens our hope that with future developments this area of work will become dipole-k_t algorithm's main forte

    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 √į√į¬•with constraints√į √į √į¬• ¬• √įand√į¬ī√į¬• = √į. 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

    Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions