1,607 research outputs found

    B flavour tagging with leptons and measurement of the CP violation phase phi_s in the B_s^0 -> J/psi phi decay at the CMS experiment

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    This thesis presents the development and optimization of an algorithm used to determine the flavour at production time of neutral B^0 and B_s^0 mesons. The flavour tagging algorithm developed in this thesis exploits muons and electrons produced in the semileptonic decay of the additional b-hadron produced in pp -> bbX collisions at the LHC. The charge of the lepton is used to infer the flavour of the neutral b-meson. Three simulated samples of B_s^0 -> J/psi phi, B^+ -> J/psi K^+ and B^0 -> J/psi K* decays are exploited to develop and test the algorithm. Two independent neural networks are defined for muons and electrons, trained on 24 000 and 20 400 simulated B_s^0 -> J/psi phi events respectively, to parametrize the probability of wrong flavour tag omega of the algorithm. The tagging performances are further measured and calibrated on a sample of self-tagging B^+ -> J/psi K^+ decays collected by the CMS experiment during 2012, corresponding to 20 fb^-1 . The charge of the kaon univocally determines the flavour of the B^+ at production time and allows the direct measure of the mis-identification probability. A tagging power P_tag = epsilon_tag (1 - 2 omega )^2 of 0.833 +/- 0.024 (stat.) +/- 0.012 (syst.) % is measured using muons and 0.483 +/- 0.020 (stat.) +/- 0.003 (syst.) % using electrons. Combining the two algorithms results in the overall tagging power of 1.307 √ā¬Ī 0.031 (stat.) √ā¬Ī 0.007 (syst.) %. The combined lepton flavour tagging algorithm is used in the measurement of the charge-parity (CP) violation parameters phi_s and DeltaGamma_s , sensitive to potential new physics processes not included in the standard model description. A time-dependent and flavour-tagged full angular analysis of the mu^+ mu^- K^+ K^- final state of the B_s^0 -> J/psi phi decay is performed based on the 2012 CMS dataset. A total of 49 000 reconstructed B_s^0 decays are used to extract the weak phase phi_s and decay with difference DeltaGamma_s values: phi_s = -0.075 +/- 0.097 (stat.) +/- 0.031 (syst.) rad DeltaGamma_s = 0.095 +/- 0.013 (stat.) +/- 0.007 (syst.) ps^-

    A fast and flexible machine learning approach to data quality monitoring

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    We present a machine learning based approach for real-time monitoring of particle detectors. The proposed strategy evaluates the compatibility between incoming batches of experimental data and a reference sample representing the data behavior in normal conditions by implementing a likelihood-ratio hypothesis test. The core model is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. The resulting algorithm is fast, efficient and agnostic about the type of potential anomaly in the data. We show the performance of the model on multivariate data from a drift tube chambers muon detector

    Using Big Data Technologies for HEP Analysis

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    The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a large amount of information. The growing size of the datasets could potentially become a limiting factor in the capability to produce scientific results timely and efficiently. Recently, new technologies and new approaches have been developed in industry to answer to the necessity to retrieve information as quickly as possible to analyze PB and EB datasets. Providing the scientists with these modern computing tools will lead to rethinking the principles of data analysis in HEP, making the overall scientific process faster and smoother. In this paper, we are presenting the latest developments and the most recent results on the usage of Apache Spark for HEP analysis. The study aims at evaluating the efficiency of the application of the new tools both quantitatively, by measuring the performances, and qualitatively, focusing on the user experience. The first goal is achieved by developing a data reduction facility: working together with CERN Openlab and Intel, CMS replicates a real physics search using Spark-based technologies, with the ambition of reducing 1 PB of public data in 5 hours, collected by the CMS experiment, to 1 TB of data in a format suitable for physics analysis. The second goal is achieved by implementing multiple physics use-cases in Apache Spark using as input preprocessed datasets derived from official CMS data and simulation. By performing different end-analyses up to the publication plots on different hardware, feasibility, usability and portability are compared to the ones of a traditional ROOT-based workflow

    Report from Working Group 3: Beyond the standard model physics at the HL-LHC and HE-LHC

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    This is the third out of five chapters of the final report [1] of the Workshop on Physics at HL-LHC, and perspectives on HE-LHC [2]. It is devoted to the study of the potential, in the search for Beyond the Standard Model (BSM) physics, of the High Luminosity (HL) phase of the LHC, defined as 33 ab‚ąí1^{-1} of data taken at a centre-of-mass energy of 14 TeV, and of a possible future upgrade, the High Energy (HE) LHC, defined as 1515 ab‚ąí1^{-1} of data at a centre-of-mass energy of 27 TeV. We consider a large variety of new physics models, both in a simplified model fashion and in a more model-dependent one. A long list of contributions from the theory and experimental (ATLAS, CMS, LHCb) communities have been collected and merged together to give a complete, wide, and consistent view of future prospects for BSM physics at the considered colliders. On top of the usual standard candles, such as supersymmetric simplified models and resonances, considered for the evaluation of future collider potentials, this report contains results on dark matter and dark sectors, long lived particles, leptoquarks, sterile neutrinos, axion-like particles, heavy scalars, vector-like quarks, and more. Particular attention is placed, especially in the study of the HL-LHC prospects, to the detector upgrades, the assessment of the future systematic uncertainties, and new experimental techniques. The general conclusion is that the HL-LHC, on top of allowing to extend the present LHC mass and coupling reach by 20‚ąí50%20-50\% on most new physics scenarios, will also be able to constrain, and potentially discover, new physics that is presently unconstrained. Moreover, compared to the HL-LHC, the reach in most observables will, generally more than double at the HE-LHC, which may represent a good candidate future facility for a final test of TeV-scale new physics

    Differential cross section measurements for the production of a W boson in association with jets in proton‚Äďproton collisions at ‚ąös = 7 TeV

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    Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript ‚ąí1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

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