7 resultados para ATLAS LHC LUCID fotomoltiplicatori caratterizzazione

em Helda - Digital Repository of University of Helsinki


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The Transition Radiation Tracker (TRT) of the ATLAS experiment at the LHC is part of the Inner Detector. It is designed as a robust and powerful gaseous detector that provides tracking through individual drift-tubes (straws) as well as particle identification via transition radiation (TR) detection. The straw tubes are operated with Xe-CO2-O2 70/27/3, a gas that combines the advantages of efficient TR absorption, a short electron drift time and minimum ageing effects. The modules of the barrel part of the TRT were built in the United States while the end-cap wheels are assembled at two Russian institutes. Acceptance tests of barrel modules and end-cap wheels are performed at CERN before assembly and integration with the Semiconductor Tracker (SCT) and the Pixel Detector. This thesis first describes simulations the TRT straw tube. The argon-based acceptance gas mixture as well as two xenon-based operating gases are examined for its properties. Drift velocities and Townsend coefficients are computed with the help of the program Magboltz and used to study electron drift and multiplication in the straw using the software Garfield. The inclusion of Penning transfers in the avalanche process leads to remarkable agreements with experimental data. A high level of cleanliness in the TRT s acceptance test gas system is indispensable. To monitor gas purity, a small straw tube detector has been constructed and extensively used to study the ageing behaviour of the straw tube in Ar-CO2. A variety of ageing tests are presented and discussed. Acceptance tests for the TRT survey dimensions, wire tension, gas-tightness, high-voltage stability and gas gain uniformity along each individual straw. The thesis gives details on acceptance criteria and measurement methods in the case of the end-cap wheels. Special focus is put on wire tension and straw straightness. The effect of geometrically deformed straws on gas gain and energy resolution is examined in an experimental setup and compared to simulation studies. An overview of the most important results from the end-cap wheels tested up to this point is presented.

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A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

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The TOTEM experiment at the LHC will measure the total proton-proton cross-section with a precision better than 1%, elastic proton scattering over a wide range in momentum transfer -t= p^2 theta^2 up to 10 GeV^2 and diffractive dissociation, including single, double and central diffraction topologies. The total cross-section will be measured with the luminosity independent method that requires the simultaneous measurements of the total inelastic rate and the elastic proton scattering down to four-momentum transfers of a few 10^-3 GeV^2, corresponding to leading protons scattered in angles of microradians from the interaction point. This will be achieved using silicon microstrip detectors, which offer attractive properties such as good spatial resolution (<20 um), fast response (O(10ns)) to particles and radiation hardness up to 10^14 "n"/cm^2. This work reports about the development of an innovative structure at the detector edge reducing the conventional dead width of 0.5-1 mm to 50-60 um, compatible with the requirements of the experiment.

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This work belongs to the field of computational high-energy physics (HEP). The key methods used in this thesis work to meet the challenges raised by the Large Hadron Collider (LHC) era experiments are object-orientation with software engineering, Monte Carlo simulation, the computer technology of clusters, and artificial neural networks. The first aspect discussed is the development of hadronic cascade models, used for the accurate simulation of medium-energy hadron-nucleus reactions, up to 10 GeV. These models are typically needed in hadronic calorimeter studies and in the estimation of radiation backgrounds. Various applications outside HEP include the medical field (such as hadron treatment simulations), space science (satellite shielding), and nuclear physics (spallation studies). Validation results are presented for several significant improvements released in Geant4 simulation tool, and the significance of the new models for computing in the Large Hadron Collider era is estimated. In particular, we estimate the ability of the Bertini cascade to simulate Compact Muon Solenoid (CMS) hadron calorimeter HCAL. LHC test beam activity has a tightly coupled cycle of simulation-to-data analysis. Typically, a Geant4 computer experiment is used to understand test beam measurements. Thus an another aspect of this thesis is a description of studies related to developing new CMS H2 test beam data analysis tools and performing data analysis on the basis of CMS Monte Carlo events. These events have been simulated in detail using Geant4 physics models, full CMS detector description, and event reconstruction. Using the ROOT data analysis framework we have developed an offline ANN-based approach to tag b-jets associated with heavy neutral Higgs particles, and we show that this kind of NN methodology can be successfully used to separate the Higgs signal from the background in the CMS experiment.

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This thesis describes methods for the reliable identification of hadronically decaying tau leptons in the search for heavy Higgs bosons of the minimal supersymmetric standard model of particle physics (MSSM). The identification of the hadronic tau lepton decays, i.e. tau-jets, is applied to the gg->bbH, H->tautau and gg->tbH+, H+->taunu processes to be searched for in the CMS experiment at the CERN Large Hadron Collider. Of all the event selections applied in these final states, the tau-jet identification is the single most important event selection criterion to separate the tiny Higgs boson signal from a large number of background events. The tau-jet identification is studied with methods based on a signature of a low charged track multiplicity, the containment of the decay products within a narrow cone, an isolated electromagnetic energy deposition, a non-zero tau lepton flight path, the absence of electrons, muons, and neutral hadrons in the decay signature, and a relatively small tau lepton mass compared to the mass of most hadrons. Furthermore, in the H+->taunu channel, helicity correlations are exploited to separate the signal tau jets from those originating from the W->taunu decays. Since many of these identification methods rely on the reconstruction of charged particle tracks, the systematic uncertainties resulting from the mechanical tolerances of the tracking sensor positions are estimated with care. The tau-jet identification and other standard selection methods are applied to the search for the heavy neutral and charged Higgs bosons in the H->tautau and H+->taunu decay channels. For the H+->taunu channel, the tau-jet identification is redone and optimized with a recent and more detailed event simulation than previously in the CMS experiment. Both decay channels are found to be very promising for the discovery of the heavy MSSM Higgs bosons. The Higgs boson(s), whose existence has not yet been experimentally verified, are a part of the standard model and its most popular extensions. They are a manifestation of a mechanism which breaks the electroweak symmetry and generates masses for particles. Since the H->tautau and H+->taunu decay channels are important for the discovery of the Higgs bosons in a large region of the permitted parameter space, the analysis described in this thesis serves as a probe for finding out properties of the microcosm of particles and their interactions in the energy scales beyond the standard model of particle physics.

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At the Tevatron, the total p_bar-p cross-section has been measured by CDF at 546 GeV and 1.8 TeV, and by E710/E811 at 1.8 TeV. The two results at 1.8 TeV disagree by 2.6 standard deviations, introducing big uncertainties into extrapolations to higher energies. At the LHC, the TOTEM collaboration is preparing to resolve the ambiguity by measuring the total p-p cross-section with a precision of about 1 %. Like at the Tevatron experiments, the luminosity-independent method based on the Optical Theorem will be used. The Tevatron experiments have also performed a vast range of studies about soft and hard diffractive events, partly with antiproton tagging by Roman Pots, partly with rapidity gap tagging. At the LHC, the combined CMS/TOTEM experiments will carry out their diffractive programme with an unprecedented rapidity coverage and Roman Pot spectrometers on both sides of the interaction point. The physics menu comprises detailed studies of soft diffractive differential cross-sections, diffractive structure functions, rapidity gap survival and exclusive central production by Double Pomeron Exchange.

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Close to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in estimating the relative rate of diffractive event categories at the LHC energies. By identifying diffractive events, detailed studies on proton structure can be carried out. The combined forward physics objects: rapidity gaps, forward multiplicity and transverse energy flows can be used to efficiently classify proton-proton collisions. Data samples recorded by the forward detectors, with a simple extension, will allow first estimates of the single diffractive (SD), double diffractive (DD), central diffractive (CD), and non-diffractive (ND) cross sections. The approach, which uses the measurement of inelastic activity in forward and central detector systems, is complementary to the detection and measurement of leading beam-like protons. In this investigation, three different multivariate analysis approaches are assessed in classifying forward physics processes at the LHC. It is shown that with gene expression programming, neural networks and support vector machines, diffraction can be efficiently identified within a large sample of simulated proton-proton scattering events. The event characteristics are visualized by using the self-organizing map algorithm.