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Search for New Physics at LHC with ATLAS Detector

Search for New Physics at LHC with ATLAS Detector. Hai-Jun Yang University of Michigan, Ann Arbor Seminar at Southern Methodist University October 20, 2008. Outline. Introduction ‘Re-discover’ the Standard Model with early LHC data Studies on vector gauge bosons

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Search for New Physics at LHC with ATLAS Detector

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  1. Search for New Physics at LHC with ATLAS Detector Hai-Jun Yang University of Michigan, Ann Arbor Seminar at Southern Methodist University October 20, 2008

  2. Outline • Introduction • ‘Re-discover’ the Standard Model with early LHC data • Studies on vector gauge bosons • Indirect Search for new physics through anomalous Triple-Gauge-Boson Couplings • Search for new physics through diboson and ttbar events • SM Higgs  WW  lnln • Z’  ttbar  bbWW bbjjln • Development of advanced particle identification algorithm • Boosted Decision Trees, Event WeightTraining Technique • A general search strategy to improve physics discovery potential • Materials presented in this talk are based on LHC physics studies by H.Yang with the Michigan ATLAS group members

  3. Standard Model Higgs Mechanism – Spontaneously break electroweak symmetry – Generate masses Gauge sector and matter sector are very successfully tested! But the Higgs sector which describes the EWSB is totally dark. To find the mystery of EWSB is one of the major motivations for experimental high energy physics (LEP, Tevatron, LHC …).

  4. SM Higgs Searches at Tevatron(Ref: arXiv:0808.0534)

  5. The Large Hadron Collider at CERNCME = 14 TeV, Lumi = 1034 cm-2 s-1 • 26.7 km Tunnel in Switzerland & France CMS pp, general purpose; HI TOTEM pp, general purpose; HI ATLAS First p-beam: Sept. 10, 2008 ALICE : HI LHCb: B-physics

  6. Proton-Proton Collisions at LHCto discover the mysteries of EWSB, Dark-Matter, …

  7. Two general purpose experiments at LHC > 10 years of hard work in design and constructions, ready for beams ATLAS CMS Length : ~45 m Diameter : ~24 m Weight : ~ 7,000 tons Electronic channels : ~ 108 Solenoid : 2 T Air-core toroids Length : ~22 m Diameter : ~14 m Weight : ~ 12,500 tons Solenoid : 4 T Fe yoke Compact and modular Excellent Standalone Muon Detector Excellent EM Calorimeter 7

  8. LHC Physics Run in 2008-2009 • Single beam injection on September 10, 2008 • pp collisions at 10 TeV start in April 2009, Luminosity would ramp up to 1033 cm-2s-1 • Integrated luminosity: a few fb-1 • Detector calibration to 1-2% accuracy • Detector performance validation by measuring cross sections of SM processes (dijets, W, Z, ttbar, diboson) • Serious searches with a few fb-1 include: • Higgs WW (MH from 150 GeV – 180 GeV) • W’ and Z’ in TeV mass region • SUSY signature

  9. Physics Reach as Integrated Lumi. Increase

  10. Re-discover Standard Model– A Steppingstone to Discover New Physics Our search for new physics at LHC will start with • W and Z productions: the standard candles • demonstrate the detector performance • constrain the PDF • Diboson (WW, WZ, ZZ, Wg, Zg) – ATL-COM-PHYS-036(041) • test the SM in high energy region • probe the anomalous triple-gauge boson couplings • understand the diboson background for new physics signature • Two methods used in the analysis • Cut-based (classical method) • Boosted Decision Trees (a new multivariate analysis tool developed at U. of Michigan by H. Yang et al.) H. Yang et.al. NIM A555 (2005)370, NIM A543 (2005)577, NIM A574(2007) 342

  11. Di-Boson Analysis – Physics Motivation H ZZ SUSY signal

  12. Diboson Results with 1fb-1 Int. Lumi Ref: ATL-COM-PHYS-2008-036, ATL-COM-PHYS-2008-041

  13. Search for new physics through anomalous TGCs with diboson events • Model independent effective Lagrangian with anomalous charged couplings LWWV/gWWV = i g1V(W†μνWμVν – W†μVνWμν) + i κV W†μWνVμν + i (λV/MW2) W†λμWνμVνλ where V = Z, γ. • In the standard model g1V = κV = 1 and λV=0.The goal is to measure these values, usually expressed as the five anomalous parameters Δg1Z, ΔκZ,λz, Δκγ,and λγ • In many cases the terms have an ŝ dependence which means the higher center-of-mass energies at the LHC greatly enhance our sensitivity to anomalous couplings • Complementary studies through different diboson channels

  14. Anomalous spectra and reweighting ratio The MT(WW) spectrum for W+W- events with anomalous coupling parameters using the BHO Monte Carlo. At right are the ‘ratios = ds(non-SM)/ds(SM)’ used to reweight fully simulated events.

  15. 2D anomalous TGC sensitivity using MT(WW) 95% C.L.contours for 0.1, 1, 10, and 30 fb-1 integrated luminosity Right: HISZ assumption (2 parameters) Bottom: “Standard” assumption,Z param. = γ param. (3 parameters)

  16. Search for New Physics with Diboson and ttbar Events • We do not really know what new physics we could discover at LHC • Many theoretical models predict that the new physics signature would show up in diboson, top-rich and large MET events. • Two examples will presented based on UM group’s studies Search for SM Higgs WW(H. Yang et.al., ATL-COM-PHYS-2008-023)

  17. Low mass region: m(H) < 2 mZ H   H  bb H   H ZZ*  4 H  WW*   or jj - Direct Search for SM H WW  lnln • Gluon-gluon fusion and WW/ZZ fusion are two dominant Higgs production mechanism

  18. MC Higgs Signal Used in Study Pythia Generator (Gluon-Gluon Fusion) H  WW  enen, mnmn, enmn Above Higgs samples were produced at UM using jobOptions similar to official jobOption DS5320 (with diff. MH and separate the ggF and VBF production) UM Pythia Higgs samples were compared to Higgs dataset 5320 by separating the ggF and the VBF events, they are in good agreement. UM samples are available at BNL Tier-1 center. 19 19

  19. MC Backgrounds Used in Study(SM samples were used for ATLAS diboson CSC note) 20 20

  20. Event Pre-selection for H WW lnln • Two leptons with opposite charges; each lepton withPT > 10 GeV • Missing ET > 15 GeV • Events must pass one of lepton trigger requirements: 2E10, 2MU6, E25I, MU20 • Physics objects: • Electron ID based on likelihood ratio > 0.6 • Muon ID based on Staco algorithm • Jet class: C4TopoJet (ET > 20 GeV) 21 21

  21. Detection Sensitivity StudiesBased on Pre-selected Events • Cut-based analysis • Optimize the straight cuts for better sensitivity • Analysis based on BoostedDecisionTrees (BDT) • Consider two leptons with 0-jet and 1-jet events • Results from cut-based and BDT analyses 22 22

  22. Select HWWlnlnwith Straight Cuts Pt (l) > 20 GeV; Max (Pt(l1),Pt(l2)) > 25 GeV Lepton Isolation In R=0.4 cone, SPt(m) < 5 GeV In R=0.4 cone, SPt(e) < 8 GeV MET > 50 GeV Njet (Et>20 GeV) = 0 or 1 Df (l1,l2) < 1.0 12 < M(l1,l2) < 50 GeV 23 23

  23. Some Variable DistributionsAfter Pre-selection 24 24

  24. Some Variable DistributionsAfter Pre-selection 10/03/2008 H. Yang - GGF H->WW H. Yang - GGF H->WW 25 25

  25. Invariant Mass of two leptons(applied all cuts except Mll cut) 26 26

  26. Results from Cut-based Analysis (1/fb) 27

  27. BDT Analysis(H. Yang et.al., ATL-COM-PHYS-2008-023) Signal for Training: PYTHIA Gluon-Gluon fusion H  WW Backgrounds for Training: WW, ttbar, WZ, W+X and Z+X Input variables for training: ET > 20 GeV 28 28

  28. Boosted Decision Trees • Relatively new in HEP – MiniBooNE, BaBar, D0(single top discovery), ATLAS • Advantages: robust, understand ‘powerful’ variables, relatively transparent,… “A procedure that combines many weak classifiers to form a powerful committee” • BDT Training Process • Split data recursively based on input variables until a stopping criterion is reached (e.g. purity, too few events) • Every event ends up in a “signal” or a “background” leaf • Misclassified events will be given larger weight in the next decision tree (boosting) H. Yang et.al. NIM A555 (2005)370, NIM A543 (2005)577, NIM A574(2007) 342

  29. A set of decision trees can be developed, each re-weighting the events to enhance identification of backgrounds misidentified by earlier trees (“boosting”) For each tree, the data event is assigned +1 if it is identified as signal, -1 if it is identified as background. The total for all trees is combined into a “score” BDT discriminator Background-like negative positive signal-like

  30. BDT Discriminator • BDT discriminator is the total • score ofthe BDT output as • shown in left plot. • Event Selection: • For 0-jet events:BDT>=200 • For 1-jet events: BDT >=220 • Detection sensitivity is defined as • Significance = NS/√NB • (With or without systematic error) 31 31

  31. Results (1/fb): Straight Cuts vs BDT Cut-based BDT-based 32 32

  32. Results (1/fb): Straight Cuts vs BDT Cut-based BDT-based 33 33

  33. Results (1/fb): Straight Cuts vs BDT Cut-based BDT-based 34 34

  34. BDT Results: H  WW  lnln (1/fb) 35 35

  35. H  WW  lnln Selection Statistical Sensitivity (1/fb) 36 36

  36. H  WW  lnln Selection Statistical Sensitivity (1/fb) 37 37

  37. Systematic Uncertainties 6.5% Luminosity uncertainty (ref. Tevatron) 5% Parton Density Function uncertainty 3% Lepton identification acceptance uncertainty 5% Energy scale uncertainty (3% on lepton energy and 10% on hadronic energy) 6% BDT training uncertainty due to energy scale uncertainty and imperfect MC cross section estimation of major backgrounds) 15% background estimation uncertainty due to limited MC data sample statistics (W/Z+X) The total systematic uncertainty from above sources is 19%. We use conservative systematic error 20% for Higgs detection significance estimation. 38

  38. Efficiency Change due to Uncertainties of Background Cross Sections To estimate systematic uncertainty caused by BDT training with imperfect MC background cross sections estimation, cross sections of main backgrounds (ww, tt) are changed by ±20% for BDT training. The relative change of background with fixed signal efficiency are listed in the table. 39

  39. Uncertainty from lepton and Jet EnergyScale and Resolution To estimate the systematic uncertainty, all energy-dependent variables in testing samples are modified by adding additional energy uncertainty, 3% for lepton and 10% for jets. The relative changes of signal and background efficienciesare calculated by using same BDT cut. 40

  40. H  WW Detection Sensitivity (1/fb, with 20% systematic error)

  41. Further Improvement • Electron-ID efficiency IsEM: 65.7% Likelihood: 78.5% BDT(UM): 82.3% BDT has high e-ID efficiency and low jet fake rate • Using B-tagging variables to suppress ttbar background • Ref: H.Yang’s talk on ‘Electron Identification Based on Boosted Decision Trees’ at ATLAS Performance and Physics Workshop on October 2, 08 http://indico.cern.ch/conferenceDisplay.py?confId=39296

  42. 2) Search for Z’  ttbar Physics motivation W / Top reconstruction from jets Event selections Z’  ttbar search strategies Expected detection sensitivities 43

  43. Physics Motivation There are many models predict the signatures with top-rich events. Z’ ttbar has been used as the benchmark for such studies. Additional U(1)' gauge symmetries and associated Z' gauge boson are one of manymotivated extensions of the SM (Ref: Paul Langacker,arXiv:0801.1345v2).Searchesfor Z’ via leptonic decay productions (ee, mm) have been conducted at LEP and Tevatron (current limit: MZ’ > 850 GeV from CDF, Ref: Phys. Rev. D70:093009, 2004). But, the searches through leptonic channels do not rule out the existence of a Z’ resonance with suppressed decays to leptons, so called “leptophobic” Z’. Several models (RS Kaluza-Klein states of gluons, weak bosons and gravitons; Topcolor leptophobic Z’; Sequential Z’ etc.) suggest that Z’-like state would decay predominantly to heavy quark-antiquark pairs, e.g. ttbar if the Z’ mass is larger than 2 Mtop. 44

  44. Search for Z’ tt at CDF stt = 7.8 ± 0.7 pb 45

  45. MC Samples Used in Our Study Signal: Z’ ttbar  bbww bbjjln Dataset: 6231, 20000 Events, M_Z’ = 1.0 TeV Dataset: 6232, 19500 Events, M_Z’ = 1.5 TeV Dataset: 6233, 20000 Events, M_Z’ = 2.0 TeV Dataset: 6234, 19500 Events, M_Z’ = 3.0 TeV Major Backgrounds: Ttbar: 5200(>=1 lep), 450100 Events Ttbar: 5204(W hadronic decay), 97750 Events Single Top: 5500(Wt,14950 Events), 5501(s-channel, 9750 Events), 5502(t-channel, 18750 Events) W/Z+Jets (1.1 Million Alpgen Events) Dijets: 5014(14500 Events), 5015 (381550 Events) 46

  46. W and Top Reconstructionwith jets final states • With the increase of Z’ mass, the energy of Top/W from Z’ decay increase and the decay jets are boosted and located in a relative small region. In order to reconstruct Top/W efficiently, it’s critical to use a suitable jet finding algorithm. • ATLAS employs two jet finding algorithms (Cone, Kt), - CJets (R=0.7) - CTopoJets (R=0.7) - C4Jets (R=0.4) - C4TopoJets (R=0.4) - Kt4Jets (R=0.4) - Kt4TopoJets (R=0.4) - Kt6Jets (R=0.6) - Kt6TopoJets (R=0.6) 47

  47. W  jj Reconstruction 48

  48. Efficiency of W  jj Reconstruction 49

  49. Mass Reconstruction of W  jj RMS of MW ~ 11 GeV 50

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