Neural Networks Search for Charged Higgs Boson of Two Doublet Higgs Model at the Hadrons Colliders

In this work, we present an analysis of a search for charged Higgs boson in the context of Two Doublet Higgs Model (2HDM) which is an extension of the Standard Model of particles physics. The 2HDM predicts by existence scalar sector with new five Higgs bosons, two of them are electrically charged and the other three Higgs bosons are neutral charged. Our analysis based on the Monte Carlo data produced from the simulation of 2HDM with proton antiproton collisions at the Tevatron $\sqrt{s}=1.96$ TeV (Fermi Lab) and proton proton collisions at the LHC $\sqrt{s}=14$ TeV (CERN) with final state includes electron , muon , multiple jets and missing transverse energy via the production and decay of the new Higgs in the hard process $pp(\bar{p})\rightarrow t\bar{t}\rightarrow H^{+}b H^{-}\bar{b}$


After the new discovery of the Standard Model Higgs boson at CERN's Large Hadron
Collider LHC on 2012 [1,2], it is now time to test possible many extensions of the The two Higgs doublet model (2HDM) can provide additional CP-violation coming from the scalar sector and can easily originate dark matter candidates, also the Minimal SuperSymmetric Model (MSSM) predicts two doublet Higgs. The 2HDMs have a richer particle spectrum with two charged and three neutral Higgs Bosons. All neutral Higgs Boson could in principle be the scalar discovered at the LHC [7][8][9]. The SM picks up the ideas of local gauge invariant and Spontaneous Symmetry Breaking (SSB) to implement a Higgs mechanism. The symmetry breaking is implemented by introducing a scalar doublet In order to induce the SSB the doublet should acquire a VEV different from zero In the next section we will present an analysis for signatures of the charged Higgs boson in the mass range 80-160 GeV using top quark pair events with a leptonically decaying in the context of 2HDM using Monte Carlo simulation programs and Artificial Neural Network (ANNs) at the LHC √ = 14 with proton-proton collisions (CMS and ATLAS detectors) and the Tevatron √ = 1.96 with proton-antiproton collisions (CDF and D0 detectors) with electron, muons, multiple jets and missing transverse energy in the final state, we assumed that the branching ratio of the charged Higgs boson to a τ lepton and a neutrino is 100%.

The Analysis
In the 2HDM, the scalar sector has two charged Higgs bosons and three neutral Higgs bosons. In current section we will present the results of Monte Carlo Simulation for production and decay the charged Higgs boson at both the LHC √ s = 14 TeV and at the Tevatron √ s = 1.96 TeV.  In the context of the Two Higgs doublet Model, the charged Higgs boson couplings are specified in terms of the electric charge and the weak mixing angle ; . The CDF detectors at Fermi Lab has reported measurements of the ̅ production cross section in the ℓ +∉ P + Q + R channels where ℓ ℓ ℓ ℓ = e, μ and where Q = ℓ ℓ ℓ ℓ is"dilepton" channel, Q = τ τ τ τ "lepton+tau", Q = one or more tagged jets ( a jet is determined to be tagged if it shows a displaced secondary vertex, these jets originate from the decay of long lived mesons such as those resulting after the hadronization process of the b quark).
The production cross-section thus depends only on the mass m M ± . The analyses are not sensitive to the quark flavour, Therefore BR (H → τ τ E ) = 10% is assumed and H H pair production leads to the final State μ ν W ν X ν X be ν Y ν X ν X b . The signal production of single charged Higgs is expected to be negligible, and the direct production of via the weak interaction is expected to have a relatively small cross section [13].
The measurements of top quark pair production cross sections tt ̅ in various channels [14]  leptophobic models extracted from cross section ratios [16] and for the tauonic model based on a measurement of the ̅ cross section in l+jets channel using topological event information [17].
The Backgrounds W+jets and the signal processes are generated with The search for the fully leptonic final state → ̅ is described in [18].
We apply the kinematics cuts on events to identify signal events. The presence of a light charged Higgs boson would result in a different distribution of ̅ events between different final states than expected in the SM. We select events with eμ with one isolated high j P electron and one muon and exactly one or at least two jets. The electron or muon had a small momentum and energy deposition, it was assumed to come from a τ decay and was therefore tagged as τ and isolated jets with an energy of at least 5 GeV, at least one and at most five charged particles and no more than ten particles in total were also considered as τ candidates [19]. In the ̅ final state the number of unknowns was higher than the number of constraints and no mass could be estimated.   [24] to be is m M ± > 76.7GeV GeV. Also a searches for the charged Higgs boson have been performed at √ = 1.8 TeV in the + Q +∉ P + ℓ and lepton decays to hadrons where ℓ = e or μ in [25] and ℓ = e, μ or τ in [26].

Neural Networks Discrimination
The neural network method used for b-tagging in the OPAL SM Higgs-boson search [27]  analysis is based on weighted event counting, with the weights computed from physical observables, also called discriminating variables of the candidate events. An improved analysis has been designed for the fully leptonic channel where BR (H → τ τ E ) = 1 and the rejection of the w w background has been refined with Artificial Neural Networks (ANNs) discrimination. When dealing with semileptonic final states, the τ τ τ τ candidate jet definition was refined removing particles that were not likely to come from τ decay.
In current work we designed an artificial neural network consists of 4 layers figure 9.
The first layer is the input layer and consists of 3 neurons (the neuron is the processing unit), the 3 neuron receive the input variables of a particle to the neural network figure 10 (Transverse momentum npt, transverse mass nmt and pseudorapidity neta). The second layer is a hidden layer consists of 5 neurons and the third layer also is a hidden layer consists of 3 neurons. The fourth layer is the output layer and consists of one neuron which gives the type of the particle gives 1 for the signal and 0 to the background as shown in figure 9. We trained and tested the neural consists of two sets, one from the LHC and the other from the Tevatron. The events of the signal and the background which we used it are stored in the Tree of ROOT data analysis. detectors) with proton-antiproton collisions at √s = 1.96 TeV using top quark pair events with a electron-muon + Jets + missing energy (µ ν µ ν τ ν τ be ν Y ν τ ν τ b ) in the final state and we assumed that the branching ratio of the charged Higgs boson to a τ lepton and a neutrino assumed Br (H → τ τ ν ) = 100%.