1,761 research outputs found

    Deep Learning fast inference on FPGA for CMS Muon Level-1 Trigger studies

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    With the advent of the High-Luminosity phase of the LHC (HL-LHC), the instantaneous luminosity of the Large Hadron Collider at CERN is expected to increase up to ‚Čą7.5‚čÖ1034cm‚ąí2s‚ąí1. Therefore, new strategies for data acquisition and processing will be necessary, in preparation for the higher number of signals produced inside the detectors. In the context of an upgrade of the trigger system of the Compact Muon Solenoid (CMS), new reconstruction algorithms, aiming for an improved performance, are being developed. For what concerns the online tracking of muons, one of the figures that is being improved is the accuracy of the transverse momentum (pT) measurement. Machine Learning techniques have already been considered as a promising solution for this problem, as they make possible, with the use of more information collected by the detector, to build models able to predict with an improved precision the pT. This work aims to implement such models onto an FPGA, which promises smaller latency with respect to traditional inference algorithms running on CPU, an important aspect for a trigger system. The analysis carried out in this work will use data obtained through Monte Carlo simulations of muons crossing the barrel region of the CMS muon chambers, and compare the results with the pT assigned by the current CMS Level 1 Barrel Muon Track Finder (BMTF) trigger system

    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