9,014 research outputs found

    Production of vector resonances at the LHC via WZ-scattering: a unitarized EChL analysis

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    In the present work we study the production of vector resonances at the LHC by means of the vector boson scattering WZ→WZWZ \to WZ and explore the sensitivities to these resonances for the expected future LHC luminosities. We are assuming that these vector resonances are generated dynamically from the self interactions of the longitudinal gauge bosons, WLW_L and ZLZ_L, and work under the framework of the electroweak chiral Lagrangian to describe in a model independent way the supposedly strong dynamics of these modes. The properties of the vector resonances, mass, width and couplings to the WW and ZZ gauge bosons are derived from the inverse amplitude method approach. We implement all these features into a single model, the IAM-MC, adapted for MonteCarlo, built in a Lagrangian language in terms of the electroweak chiral Lagrangian and a chiral Lagrangian for the vector resonances, which mimics the resonant behavior of the IAM and provides unitary amplitudes. The model has been implemented in MadGraph, allowing us to perform a realistic study of the signal versus background events at the LHC. In particular, we have focused our study on the pp→WZjjpp\to WZjj type of events, discussing first on the potential of the hadronic and semileptonic channels of the final WZWZ, and next exploring in more detail the clearest signals. These are provided by the leptonic decays of the gauge bosons, leading to a final state with ℓ1+ℓ1−ℓ2+νjj\ell_1^+\ell_1^-\ell_2^+\nu jj, ℓ=e,μ\ell=e,\mu, having a very distinctive signature, and showing clearly the emergence of the resonances with masses in the range of 1.5-2.5 TeV, which we have explored.Comment: Revised version accepted for publication in JHEP. Enlarged analysis. References added. 44 pages, 23 figures, 3 table

    Setting up tunneling conditions by means of Bohmian mechanics

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    Usually tunneling is established after imposing some matching conditions on the (time-independent) wave function and its first derivative at the boundaries of a barrier. Here an alternative scheme is proposed to determine tunneling and estimate transmission probabilities in time-dependent problems, which takes advantage of the trajectory picture provided by Bohmian mechanics. From this theory a general functional expression for the transmission probability in terms of the system initial state can be reached. This expression is used here to analyze tunneling properties and estimate transmissions in the case of initial Gaussian wave packets colliding with ramp-like barriers.Comment: 18 pages, 4 figure

    Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps

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    The Independent Component Analysis (ICA) algorithm is implemented as a neural network for separating signals of different origin in astrophysical sky maps. Due to its self-organizing capability, it works without prior assumptions on the signals, neither on their frequency scaling, nor on the signal maps themselves; instead, it learns directly from the input data how to separate the physical components, making use of their statistical independence. To test the capabilities of this approach, we apply the ICA algorithm on sky patches, taken from simulations and observations, at the microwave frequencies, that are going to be deeply explored in a few years on the whole sky, by the Microwave Anisotropy Probe (MAP) and by the {\sc Planck} Surveyor Satellite. The maps are at the frequencies of the Low Frequency Instrument (LFI) aboard the {\sc Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic diffuse emissions from thermal dust and synchrotron. We show that the ICA algorithm is able to recover each signal, with precision going from 10% for the Galactic components to percent for CMB; radio sources are almost completely recovered down to a flux limit corresponding to 0.7σCMB0.7\sigma_{CMB}, where σCMB\sigma_{CMB} is the rms level of CMB fluctuations. The signal recovering possesses equal quality on all the scales larger then the pixel size. In addition, we show that the frequency scalings of the input signals can be partially inferred from the ICA outputs, at the percent precision for the dominant components, radio sources and CMB.Comment: 15 pages; 6 jpg and 1 ps figures. Final version to be published in MNRA
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