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Register a new userDeep Neural Network application: Higgs boson CP state mixing angle in H to tau tau decay and at LHC
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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.
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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).
In phenomenological preparation for new measurements one searches for the carriers of quality signatures. Often, the first approach quantities may be difficult to measure or to provide sufficiently precise predictions for comparisons. Complexity of necessary details grow with precision. To achieve the goal one can not break the theory principles, and take into account effects which could be ignored earlier. Mixed approach where dominant effects are taken into account with intuitive even simplistic approach was developed. Non dominant corrections were controlled with the help of Monte Carlo simulations. Concept of Optimal Variables was successfully applied for many measurements. New techniques, like Machine Learning, offer solutions to exploit multidimensional signatures. Complementarity of these new and old approaches is studied for the example of Higgs Boson CP-parity measurements in H to tau^+tau^-, tau^pm to nu (3pi)^pm cascade decays.
In this paper, we discuss application of the TauSpinner package as a simulation tool for measuring the CP state of the newly discovered Higgs boson using the transverse spin correlations in the H to tau tau decay channel. We discuss application for its main background Z/gamma* to tau tau as well. The TauSpinner package allows one to add, with the help of weights, transverse spin correlations corresponding to any mixture of scalar/pseudoscalar state, on already existing events using information from the kinematics of outgoing tau leptons and their decay products only. This procedure can be used when polarimetric vectors of the taus decays and density matrix for tau-pair production are not stored with the event sample. We concentrate on the well-defined effects for the Higgs (or Higgs-like scalar) decays, which are physically separated from the production processes. TauSpinner also allows to reintroduce (or remove) spin correlations to events from Drell-Yan Z/gamma* to tau tau process, the main background for the Higgs parity observables, again with the help of weights only. From the literature, we recall well-established observables, developed for measuring the CP of the Higgs, and use them as benchmarks for illustrating applications of the TauSpinner package. We also include a description of the code and prepared testing examples.
The issue of Hermiticity of the Higgs boson interaction with fermions is addressed. A model for non-Hermitian Yukawa interaction is proposed and approximation of one fermion generation is considered. Symmetry properties of the corresponding $h f bar{f}$ Lagrangian with respect to the discrete P, C and T transformations are analyzed, and the modified Dirac equation for the free fermion is studied. Longitudinal polarization of the fermions in the decay $h to f bar{f}$, which arises due to non-Hermiticity of the $h f bar{f}$ interaction, is discussed. It is suggested to study effects of this non-Hermiticity in the decay $h to tau^- tau^+ to mu^- {bar u}_mu u_tau , mu^+ u_mu {bar u}_tau$, for which observables (asymmetries) are constructed which take nonzero values for a non-Hermitian $h tau^- tau^+$ interaction. These asymmetries are analyzed for various configurations of the muon energies.
We investigate the prospects of discovering the top quark decay into a charm quark and a Higgs boson ($t to c h^0$) in top quark pair production at the CERN Large Hadron Collider (LHC). A general two Higgs doublet model is adopted to study flavor changing neutral Higgs (FCNH) interactions. We perform a parton level analysis as well as Monte Carlo simulations using textsc{Pythia}~8 and textsc{Delphes} to study the flavor changing top quark decay $t to c h^0$, followed by the Higgs decaying into $tau^+ tau^-$, with the other top quark decaying to a bottom quark ($b$) and two light jets ($tto bWto bjj$). To reduce the physics background to the Higgs signal, only the leptonic decays of tau leptons are used, $tau^+tau^- to e^pmmu^mp +slashed{E}_T$, where $slashed{E}_T$ represents the missing transverse energy from the neutrinos. In order to reconstruct the Higgs boson and top quark masses as well as to effectively remove the physics background, the collinear approximation for the highly boosted tau decays is employed. Our analysis suggests that a high energy LHC at $sqrt{s} = 27$ TeV will be able to discover this FCNH signal with an integrated luminosity $mathcal{L} = 3$ ab$^{-1}$ for a branching fraction ${cal B}(t to ch^0) agt 1.4 times 10^{-4}$ that corresponds to a FCNH coupling $|lambda_{tch}| agt 0.023$. This FCNH coupling is significantly below the current ATLAS combined upper limit of $|lambda_{tch}| = 0.064$.
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