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Register a new userDiscriminating between SUSY and Non-SUSY Higgs Sectors through the Ratio $H to b bar b / H to tau^+ tau^-$ with a 125 GeV Higgs boson
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It is still an open question whether the new scalar particle discovered at the LHC with a mass of 125 GeV is the SM Higgs boson or it belongs to models of new physics with an extended Higgs sector, as the MSSM or 2HDM. The ratio of branching fractions $R$ = BR($H to b bar b$)/BR($H to tau^+ tau^-$) of Higgs boson decays is a powerful tool in order to distinguish the MSSM Higgs sector from the SM or non-supersymmetric 2HDM. This ratio receives large renormalization-scheme independent radiative corrections in supersymmetric models at large $tanbeta$, which are insensitive to the SUSY mass scale and absent in the SM or 2HDM. Making use of the current LHC data and the upcoming new results on Higgs couplings to be reported by ATLAS and CMS collaborations and in a future linear collider, we develop a detailed and updated study of this ratio $R$ which improves previous analyses and sets the level of accuracy needed to discriminate between models.
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We study the one loop electroweak radiative corrections to $h^0to bbar{b}$ and $h^0to tau^+tau^-$ in the framework of two Higgs doublet Model (2HDM). We evaluate the deviation of these couplings from their Standard Model (SM) values. $h^0to bbar{b}$ and $h^0to tau^+tau^-$ may receives large contribution from triple couplings $h^0H^0H^0$, $H^0h^0h^0$, $h^0A^0A^0$ and $h^0H^+H^-$ which are absent in the Standard Model. It is found that in 2HDM, these corrections could be significant and may reach more than 20% for not tow heavy $H^0$ or $A^0$ or $H^pm$. We also study the ratio of branching ratios $R=BR(h^0to bbar{b})/BR(h^0to tau^+tau^-)$ of Higgs boson decays which could be used to disentangle SM from other models such as 2HDM.
We study effects of charged Higgs boson exchange in $bar B to D tau bar u_{tau}$. The Yukawa couplings of Model II of two-Higgs-doublet model, which has the same Yukawa couplings as MSSM, is considered. We evaluate the decay rate including next-to-leading QCD corrections and estimate uncertainties in the theoretical calculation. Our analysis will contribute to probe an extended Higgs sector at B factory experiments.
Machine Learning (ML) techniques are rapidly finding a place among the methods of High Energy Physics data analysis. Different approaches are explored concerning how much effort should be put into building high-level variables based on physics insight into the problem, and when it is enough to rely on low-level ones, allowing ML methods to find patterns without explicit physics model. In this paper we continue the discussion of previous publications on the CP state of the Higgs boson measurement of the H to tau tau decay channel with the consecutive tau^pm to rho^pm nu; rho^pm to pi^pm pi^0 and tau^pm to a_1^pm nu; a_1^pm to rho^0 pi^pm to 3 pi^pm cascade decays. The discrimination of the Higgs boson CP state is studied as a binary classification problem between CP-even (scalar) and CP-odd (pseudoscalar), using Deep Neural Network (DNN). Improvements on the classification from the constraints on directly non-measurable outgoing neutrinos are discussed. We find, that once added, they enhance the sensitivity sizably, even if only imperfect information is provided. In addition to DNN we also evaluate and compare other ML methods: Boosted Trees (BT), Random Forest (RF) and Support Vector Machine (SVN).
The consecutive steps of cascade decay initiated by H to tau tau can be useful for the measurement of Higgs couplings and in particular of the Higgs boson parity. In the previous papers we have found, that multi-dimensional signatures of the tau^pm to pi^pm pi^0 nu and tau^pm to 3pi^pm nu decays can be used to distinguish between scalar and pseudoscalar Higgs state. The Machine Learning techniques (ML) of binary classification, offered break-through opportunities to manage such complex multidimensional signatures. The classification between two possible CP states: scalar and pseudoscalar, is now extended to the measurement of the hypothetical mixing angle of Higgs boson parity states. The functional dependence of H to tau tau matrix element on the mixing angle is predicted by theory. The potential to determine preferred mixing angle of the Higgs boson events sample including $tau$-decays is studied using Deep Neural Network. The problem is adressed as classification or regression with the aim to determine the per-event: a) probability distribution (spin weight) of the mixing angle; b) parameters of the functional form of the spin weight; c) the most preferred mixing angle. Performance of methods are evaluated and compared. Numerical results are collected.
We evaluate long-distance electromagnetic (QED) contributions to $bar{B}{}^0 to D^+ tau^{-} bar{ u}_{tau}$ and $B^- to D^0 tau^{-} bar{ u}_{tau}$ relative to $bar{B}{}^0 to D^+ mu^{-} bar{ u}_{mu}$ and $B^- to D^0 mu^{-} bar{ u}_{mu}$, respectively, in the standard model. We point out that the QED corrections to the ratios $R(D^{+})$ and $R(D^{0})$ are not negligible, contrary to the expectation that radiative corrections are almost canceled out in the ratio of the two branching fractions. The reason is that long-distance QED corrections depend on the masses and relative velocities of the daughter particles. We find that theoretical predictions for $R(D^{+})^{tau/mu}$ and $R(D^{0})^{tau/mu}$ can be amplified by $sim4%$ and $sim3%$, respectively, for the soft-photon energy cut in range $20$-$40$ MeV.
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