CMS High mass WW and ZZ Higgs search with the complete LHC Run1 statistics

A search for the decay of a heavy Higgs boson in the H$\to$ZZ and H$\to$WW channels is reported, analyzing several final states of the H$\to$ZZ and H$\to$WW decays. The search used proton-proton collision data corresponding to an integrated luminosity of up to 5.1 fb$^{-1}$ at $\sqrt{s} = 7$ TeV and up to 19.7 fb$^{-1}$ at $\sqrt{s} = 8$ TeV recorded with the CMS experiment at the CERN LHC. A Higgs boson with Standard Model-like coupling and decays in the mass range of 145 $< m_H <$ 1000 GeV is excluded at 95\% confidence level, based on the limit on the product of cross section and branching fraction. An interpretation of the results in the context of an electroweak singlet extension of the standard model is reported.Comment: 6 pages, 2 figures, to appear in the proceedings of the 50th Rencontres de Moriond, Electroweak session, 201

An alternative wind profile formulation for urban areas in neutral conditions

On the basis of meteorological observations conducted within the city of Rome, Italy, a new formulation of the wind-speed profile valid in urban areas and neutral conditions is developed. It is found that the role played by the roughness length in the canonical log-law profile can be taken by a local length scale, depending on both the surface cover and the distance above the ground surface, which follows a pattern of exponential decrease with height. The results show that the proposed model leads to increased performance compared with that obtained by using other approaches found in the literature

The Gram-Charlier method to evaluate the probability density function in monodimensional case

In many experimental applications, starting from a random variable, it is possible to evaluate the moments and to define the probability density function(PDF) in different ways. In this paper a new approach is shown in order to estimate the PDF by moments according to Gram-Charlier method (GCm). The approach consists of a choice of standard deviation (s new) in GCm which optimizes the values of the input moments. In particular three s new are selected in order to minimize: 1) the sum of absolute relative deviations among theoretical and experimental moments; 2) the relative per cent of negative probabilities coming from GC expansion; 3) the product between the two previous functions. A theoretical application of the above approach is made where the input moments data set comes from the vertical velocity distribution estimated for one level of the convective mixed layer. This application consists of two different simulations. The first evaluates the moments up to 10th order, having as input data the moments up to 3rd order. The second gives the moments up to 10th order considering both the moments of the previous simulation and the 4th-order moment calculated with Gaussian closure as input data

Measurement of the Higgs properties at CMS

The studies of the properties of the recently found boson performed by CMS are presented. The analyses reported here use the data sample of 5.1 fb−1 at √s = 7TeV and 12.1 fb−1 at √s = 8TeV delivered by LHC and collected by the CMS experiment. The background-only hypothesis is excluded with a 6.9σ significance. The mass of the new boson is measured to be 125.8 ± 0.4(stat) ± 0.4(syst) GeV/c2, combining the diphoton and four lepton channels. Several spin and intrinsic parity hypotheses are tested. The SM coupling structure is tested combining the measurements in all the considered final states, and a good Agreement is found with the Standard Model predictions

A new formulation of the Gram-Charlier method: Performance for fitting non-normal distribution

The Gram-Charlier expansion was derived in an attempt to express non-normal densities as infinite series involving the normal density and its derivatives, using the moments data as input terms. In classic Gram-Charlier expansion the random variable is standardized, so that the Gaussian parameters are Always fixed and referred to the mean equal to zero and to the standard deviation equal to one. This assumption seems to be too strong. An improvement of Gram-Charlier expansion was obtained by an optimization process, directed to choose new values of Gaussian parameters. In order to check the performance of the new approach, an estimate of the gamma probability density function was calculated. Two probability density functions, characterized by a different degree of skewness and kurtosis, were considered. The study has shown that in comparison with the classic assumption, the new one always gives the best results in terms of probability density function reproducibility and allows the best evaluation of the input moments. Further the comparison between estimated moments of order higher than the input ones and the theoretical moments shows a good reproduction. Finally the method seems to suggest that a less restrictive condition can be considered respect to the usual convergence criterium of the Gram-Charlier expansion

Air pollution model and neural network: An integrated modelling system

It is well known that neural networks can work as universal approximators of non-linear functions and they have become a useful tool either where any precise phenomenological model is available or when uncertainty complicates the application of deterministic modelling as, for example, in environmental systems. Usually, NN models are using as regression tool. We have developed an integrated modelling system coupling an air dispersion model with a neural network method both to simulate the influence of important parameters on air pollution models and to minimize the input neural net variables. In our approach, an optimised 3-Layer Perception is used to filter the air pollution concentrations evaluated by means of the non-Gaussian analytical model ADMD. We applied this methodology to the wellknown Indianapolis urban data set which deals with a release of pollutants from an elevated emission source