1,541 research outputs found

    Search for a Standard Model Higgs boson decaying to b quarks and produced in association with Z/W bosons with the CMS detector

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    A search for the standard model Higgs boson is performed in a data sample corresponding to an integrated luminosity of 1.1 fb−1^{-1}, recorded by the CMS detector in proton-proton collisions at the LHC with a 7 TeV center-of-mass energy. The following modes are studied: W(ΌΜ\mu \nu)H, W(eÎœ\nu)H, Z(ΌΌ\mu \mu)H, Z(ee)H and Z(ΜΜ\nu \nu)H, with the Higgs decaying to bb pairs. 95% C.L. upper limits on the VH production cross section are derived for a Higgs mass between 110 and 135 GeV. The expected (observed) upper limit at 115 GeV is found to be 5.7 (8.3) times the standard model expectation.Comment: Presented at the 2011 Hadron Collider Physics symposium (HCP-2011), Paris, France, November 14-18 2011, 4 pages, 3 figure

    Study the effect of beam energy spread and detector resolution on the search for Higgs boson decays to invisible particles at a future e+^+e−^- circular collider

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    We study the expected sensitivity to measure the branching ratio of Higgs boson decays to invisible particles at a future circular \epem collider (FCC-ee) in the process e+e−→HZe^+e^-\to HZ with Z→ℓ+ℓ−Z\to \ell^+\ell^- (ℓ=e\ell=e or ÎŒ\mu) using an integrated luminosity of 3.5 ab−1^{-1} at a center-of-mass energy s=240\sqrt{s}=240 GeV. The impact of the energy spread of the FCC-ee beam and of the resolution in the reconstruction of the leptons is discussed. %Two different detector concepts are considered: a detector corresponding to the CMS reconstruction performances and the expected design of the ILC detector. The minimum branching ratio for a 5σ5\sigma observation after 3.5ab−1^{-1} of data taking is 1.7±0.1%(stat+syst)1.7\pm 0.1\%(stat+syst) . The branching ratio exclusion limit at 95\% CL is 0.63±0.22%((stat+syst))0.63 \pm 0.22\%((stat+syst)).Comment: 17 pages, submitted to EPJ

    First experience in operating the population of the condition databases for the CMS experiment

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    Reliable population of the condition databases is critical for the correct operation of the online selection as well as of the offline reconstruction and analysis of data. We will describe here the system put in place in the CMS experiment to populate the database and make condition data promptly available both online for the high-level trigger and offline for reconstruction. The system, designed for high flexibility to cope with very different data sources, uses POOL-ORA technology in order to store data in an object format that best matches the object oriented paradigm for \texttt{C++} programming language used in the CMS offline software. In order to ensure consistency among the various subdetectors, a dedicated package, PopCon (Populator of Condition Objects), is used to store data online. The data are then automatically streamed to the offline database hence immediately accessible offline worldwide. This mechanism was intensively used during 2008 in the test-runs with cosmic rays. The experience of this first months of operation will be discussed in detail.Comment: 15 pages, submitter to JOP, CHEP0

    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 ð„ „ ðandðŽð„ = 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

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