Separating Electroweak and Strong interactions in Drell-Yan processes at LHC: leptons angular distributions and reference frames

Among the physics goals of LHC experiments, precision tests of the Standard Model in the Strong and Electroweak sectors play an important role. Because of nature of the proton-proton processes, observables based on the measurement of the direction and energy of leptons provide the most precise signatures. In the present paper, we concentrate on the angular distribution of Drell-Yan process leptons, in the lepton-pair rest-frame. The vector nature of the intermediate state imposes that distributions are to a good precision described by spherical polynomials of at most second order. We show that with the proper choice of the coordinate frames, only one coefficient in this polynomial decomposition remains sizable, even in the presence of one or two high $p_T$ jets. The necessary stochastic choice of the frames relies on probabilities independent from any coupling constants. This remains true when one or two partons accompany the lepton pairs. In this way electroweak effects can be better separated from strong interaction ones for the benefit of the interpretation of the measurements. Our study exploits properties of single gluon emission matrix elements which are clearly visible if a conveniently chosen form of their representation is used. We rely also on distributions obtained from matrix element based Monte Carlo generated samples of events with two leptons and up to two additional partons in test samples. Incoming colliding protons' partons are distributed accordingly to PDFs and are strictly collinear to the corresponding beams.Comment: 22 pages 9 figure

Prospect for the Higgs searches with the ATLAS detector

The investigation of the electroweak symmetry breaking is one of the primary tasks of the experiments at the CERN Large Hadron Collider (LHC). The potential of the ATLAS experiment for the discovery of the Higgs boson(s) in Standard Model and Minimal Supersymmetric Standard Model is presented, with emphasis on studies which have been completed recently.Comment: Presented at Cracow Epiphany Conference on Hadron Interactions at the Dawn of the LHC, dedicated to memory of J. Kwiecinski, Krakow, Poland, 5-7 January 2009, 22page

The tauola-photos_F environment for versioning the TAUOLA and PHOTOS packages

We present the system for versioning two packages: the TAUOLA of tau lepton decay and PHOTOS for radiative corrections in decays. The following features can be chosen in automatic or semi-automatic way: (1) format of the common block HEPEVT; (2) version of the physics input (for TAUOLA): as published, as initialized by CLEO collaboration, as initialized by ALEPH collaboration (it is suggested to use this version only with the help of the collaboration advice); (3) type of application: stand-alone, universal interface through HEPEVT, interface for KKMC Monte Carlo; (4) random number generators; (5) compiler options.Comment: nine pages, late

Production of tau tau jj final states at the LHC and the TauSpinner algorithm: the spin-2 case

The TauSpinner algorithm is a tool that allows to modify the physics model of the Monte Carlo generated samples due to the changed assumptions of event production dynamics, but without the need of re-generating events. With the help of weights $\tau$-lepton production or decay processes can be modified accordingly to a new physics model. In a recent paper a new version TauSpinner ver.2.0.0 has been presented which includes a provision for introducing non-standard states and couplings and study their effects in the vector-boson-fusion processes by exploiting the spin correlations of $\tau$-lepton pair decay products in processes where final states include also two hard jets. In the present paper we document how this can be achieved taking as an example the non-standard spin-2 state that couples to Standard Model particles and tree-level matrix elements with complete helicity information included for the parton-parton scattering amplitudes into a $\tau$-lepton pair and two outgoing partons. This implementation is prepared as the external (user provided) routine for the TauSpinner algorithm. It exploits amplitudes generated by MadGraph5 and adopted to the TauSpinner algorithm format. Consistency tests of the implemented matrix elements, reweighting algorithm and numerical results for observables sensitive to $\tau$ polarization are presented.Comment: 17 pages, 6 figures; version published in EPJ

What is the W b anti-b, Z b anti-b or t anti-t b anti-b irreducible background to the light Higgs boson searches at LHC?

The W b anti-b, Z b anti-b and t anti-t b anti-b production at LHC are irreducible backgrounds for possible observability of the Standard Model (SM) and Minimal Supersymmetric Standard Model (MSSM) light Higgs boson respectively in the associated WH, ZH and t anti-t H production followed by the H -> b anti-b decay. We present a comparison of the background estimates as obtained with (a) complete massive matrix element implemented in AcerMC Monte Carlo generator and (b) PYTHIA implementation of the inclusive W, Z, and t anti-t production, followed by the parton showering mechanism. Both approaches lead to a production of the final state of interest, but differ in the approximations used. We concentrate on the comparison of these approaches for the background to the light Higgs boson searches at LHC.Comment: EPJC Referee's comments adde

Application of TauSpinner for studies on tau-lepton polarization and spin correlations in Z, W and H decays at LHC

The tau-lepton plays an important role in the physics program at LHC. Its spin can be used for separation of signal from background or in measuring properties of New Particles decaying to tau leptons. The TauSpinner package represents a tool to modify tau spin effects in any sample containing tau leptons. Generated events, featuring taus produced from intermediate state W, Z, H bosons can be used as an input. The information on the polarization and spin correlations is reconstructed from the kinematics of the tau lepton(s) (nutau in case of W-mediated processes) and tau decay products. By weights, attributed on the event-by-event basis, it enables numerical evaluation and/or modification of the spin effects. We review distributions to monitor spin effects in leptonic and hadronic tau decays with up to three pions, to provide benchmarks for validation of spin content of the event sample and to visualize the tau lepton spin polarization and correlation effects. The demonstration examples for use of TauSpinner libraries, are documented. New validation methods of such an approach are provided. Other topics, like TauSpinner systematic errors or sensitivity of experimental distributions to spin, are addressed in part only. This approach is of interest for implementation of spin effects in embedded tau lepton samples, where Z to mu mu events from data of muons are replaced by simulated tau leptons. Embedding is used at LHC for estimating Z to tau tau background to H to tau tau signatures.Comment: 1+41 pages, 5 figures in main text, multitude of figures in appendice

Machine learning classification: case of Higgs boson CP state in H to tau tau decay at LHC

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).Comment: 1+20 pages, 9 figures, 6 tables, extended content and improved readabilit