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Search for Standard Mod el Higgs in Two Photon Final State at ATLAS

Search for Standard Mod el Higgs in Two Photon Final State at ATLAS. HYEON JIN KIM JUNE 25, 2010. Outline. Standard Model and Higgs Boson ATLAS at the LHC Photon and Electron Identification (ID) in ATLAS with a Covariant Matrix based Method (H-matrix)

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Search for Standard Mod el Higgs in Two Photon Final State at ATLAS

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  1. Search forStandard Model Higgsin TwoPhotonFinal State at ATLAS HYEON JIN KIM JUNE 25, 2010

  2. Outline • Standard Model and Higgs Boson • ATLAS at the LHC • Photon and Electron Identification (ID) in ATLAS with a Covariant Matrix based Method (H-matrix) • A Data Driven Method for Photon Identification Efficiency Measurement • Photons Showers in ATLAS Cosmic-ray Muon Data • Prospect for Higgs Search using H➝  • Conclusions Search for H → γ γ

  3. STANDARD MODEL AND HIGGS BOSON

  4. Standard Model • The Standard Modelof particle physics describes elementary particles and how they interact. • Matter is made of fermions. ✒ Leptons and quarks • The interactions between elementary particles ✒ The electromagnetic, the strong and the weak interactions ✒ mediated by particles called gauge bosons. • Gauge invariance requires all these particles to be massless! ✒ Experimental values of the masses of the W and Z gauge bosons suggest otherwise. ✒∼85-90 times the mass of a proton Search for H → γ γ

  5. Higgs Mechanism • Higgsmechanismcangivemass to W, Z bosonswithoutbreaking gauge invariance. ✒ It keeps the photon massless. • The Higgs boson has not yet been observed experimentally. ✒ The search for the Higgs boson is one of the most important goals of the ATLAS experiment at the Large Hadron Collider (LHC). • Despite the prediction of Higgs, the theory does not provide a direct estimate of its mass. ✒ The LEP experiments have set a 95% confidence level (CL) lower limit on the Higgs mass: mH > 114.4 GeV @ 95% CL. Search for H → γ γ

  6. Higgs production & decay mode at LHC Gluon Fusion • Large center of mass energy ✒Gluon fusion is the dominant production channel over the whole range • H ➝ γγ has relatively small branching ratio but a clean signature with two back-to-back photons ✒ The EM calorimeter identify electrons and photons against overwhelming background from hadronic jets Vector Boson Fusion Search for H → γ γ

  7. ATLAS at the LHC

  8. Lake of Geneva CMS Airport LHCb ALICE ATLAS LHC (Large Hadron Collider) • s = 14 TeV(7 times higher than Tevatron) • search for new massive particles up to m ~ 5 TeV • Ldesign = 1034 cm-2 s-1 (>102 higher than Tevatron) • search for rare processes with smallσ (N = Lσ ) Search for H → γ γ

  9. ATLAS (A Toroidal LHC Aparatus) Installed just across the CERN main site, 92 m below ground. Tile barrel Tile extended barrel LAr EM end-cap Proton Beam Proton Beam LArhadronic end-cap LAr EM barrel LAr forward calorimeter Search for H → γ γ

  10. Electromagnetic (EM) Calorimeter accordion-shaped Measure energy and direction of  & e • Presampler(|| < 1.8) ✒ correct for energy lost in dead material in front of calorimeter. • The barrel EM calorimeter (||<1.475) ✒ 1st layer :/0 separation,  position measurement ✒ 2nd layer :main energy measurement ✒ 3rd layer : high energy shower tails Hadron/EM separation • The end-cap calorimeter (1.375<||< 3.2) Search for H → γ γ

  11. PHOTON AND ELECTRON IDENTIFICATION IN ATLAS WITH A COVARIANT MATRIX BASED METHOD (H-matrix)

  12. Motivation • e/ identification with high efficiency and high rejection against jets is crucial for H ➝ search • Measure and understand e/ ID efficiencies and background rejection ✒ Improve Higgs search efficiency • Selection of e/ from jetsis based on & their characteristic features in EM calorimeter. • Covariant matrix technique (H-matrix ) w/ used at DØ for e-ID ✒ Used EM shower shape correlations ✒ Proved to be a great tool for e/ and hadrons separation • Benefit from fine cell sizes of ATLAS Calorimeter • Improve e/ ID by generating a 2 quantity utilizing H-matrix technique Search for H → γ γ

  13. Principle of H-matrix • H-Matrix exploits the correlation in transverse and longitudinal electromagnetic shower shapes. • The correlations between the variables are reflected through the covariant matrix, M, whose elements are • e/-likeness is presented by χ2 a given candidate object m. where, Hij (covariant matrix)-1and yi is discriminating variables. • A shower that closely resembles an e or  shower will have a m2 ~ n dim. χγ2 Search for H → γ γ

  14. Discriminating Variables (i) • Longitudinal Variables ✒ Fractional energies in each layer of EM cal (fi, i =0~3). ✒ Fractional energy in 1st layer of hadronic cal (f4) • Transverse Variables ✒ Fractional energy in shower core (R37). ✒ The second layer of EM calorimeter a. The Ratio of energy in 3x7 over 7x7 (R) & in 3x3 over 3x7 (Rφ) b. Lateral width in (ω2) f4 ω2 R f2 Search for H → γ γ

  15. Discriminating Variables (ii) ΔE = Emin – Emax2 • Transverse Variables • ✒ The first layer of EM calorimeter • a. Shower width over 3 strips around maximal energy deposit (ω3stips) • b. Shower width over 20 strips (ωtot1) • c. Energy fraction outside of shower core (Fside) • d. Energydifference (ΔE) & fractional energy of 2nd maximal energy (Rmax2) in 1st layer EM calorimeter Fside Rmax2 ω3strips Search for H → γ γ

  16. Mean values & Covariant Matrix M • Build H-matrix separately for e and  ✒ The shower shapes are different b/w electron and photon. ✒ The single electron and photon MC samples • The discriminating variables have energy and position (in η) dependences • The covariant matrix is parameterized by using energy & η. 200 GeV electrons Photons at 1.52 < |η| < 1.8 Search for H → γ γ

  17. Available instrumentation in  region • 12 subdivisions of  based on granularities & the thickness of absorber in EM calorimeter. Search for H → γ γ

  18. Parameterization • Mean values are parameterized as function of energy. ✒ f3 : ✒ others : ✒ f4, ΔE and Rmax2: Linear interpolation between the two adjacent energy points • Determine the energy dependence of M ✒ Linear interpolation between the two adjacent energy points Single electrons samples at 0.6 < ||< 0.8 1.0 < ||< 1.2 Search for H → γ γ

  19. H-matrix for Background • To enhance H-matrix performance, H-matrix is need to be optimized using information of both signal and background (i.e. jets) ✒ Log-likelihood ratio : the exact shapes of background for p.d.f. construction ✒ Cut-based algorithm: sets the cuts values by looking at both the signal and backgrounds shapes • To incorporate background shape, H-matrix for background is built. • γ-jet samples in different ET ranges are used for jet H-matrix. • Photon H-matrix incorporate jet H-matrix. ✒ χ2 = ½ (χγ2 -χjet2) for combined photon and jet H-matrix Jet H-matrix Obtained from H → γγ (mH = 120 GeV) & dijet samples χjet2 Search for H → γ γ

  20. H-matrix Performance • Efficiency and rejection ✒ Efficiency (ε) = ✒ Rejection = • Samples : generated by pythia and full detector simulation ✒ Z→ee ✒ H →γγ with mH = 120 GeV ✒ Highly EM dijet sample • Using means values of shower variables and covariant matrix M, χ2 is • calculated by Photon-jet H-matrix Photon H-matrix Electron H-matrix χγ2 χe2 Search for H → γ γ

  21. Electron H-matrix Performance • H-matrix performance compared to cut-based method ✒ The tune ofχe2cut values in different ET bins ✒ Provides the same efficiency at the cut-based in each ETbin. • Rejection power calculated ✒ H-matrix shows better rejection. Search for H → γ γ

  22. Photon–jet H-matrix Performance • Efficiency change with ET ✒ Adjust the χγ2 cut value in different ET bins to make the efficiency constant with respect to ET of the photon. • Tuned χ2 cut values to give same efficiency as cut-based algorithm ✒ Its performance equivalent to that of cut-based algorithm. Photon H-matrix Photon–jet H-matrix Photon-jet H-matrix Combined photon and jet H-matrix enhance photon H-matrix performance. Search for H → γ γ

  23. Systematic Uncertainty • Effect of data to simulation • discrepancies in shower shapes • ✒ Shower property differ in data from their • distribution from simulation • ✒ Measure the potential effect of data to • simulation discrepancies on the performance • of the H-matrix • Effect ofdifferent EM scales in data and • simulation • ✒ EM scale uncertainty is known to about 2% • In early period of ATLAS data taking. • ✒ Emeasured /Etrue is 1.00 ±0.02 Discrepancies : 0.5% ~ 5% Emeasured = Etrue (1+0.02) Emeasured = Etrue (1- 0.02) Search for H → γ γ

  24. A DATA DRIVEN METHOD FOR PHOTON IDENTIFICATION EFFICIENCY MEASUREMENT

  25. Motivation • Pure photon sample is important ✒ To measure photon efficiency ✒ To understand shower shapes • No known physics process to give pure photon samples. • Z→μμγis source of pure photons at high center of mass and luminosity. • This method tested by using Z→μμMC sample • Z→μμγ events in Z→μμare selected by : ✒ Photon non collinear to muons ✒ Invariant mass cut of 2 muons and photon 3-body decay ISR (Initial state radiation) FSR (Final state radiation) γradiation Search for H → γ γ

  26. Simulation Samples and Event Selection • Sample (√s = 10 TeV) ✒ Signal : Z→μμ generated by pythia , alpgen and full detector simulation ✒ Background • tt (mc@nlo + jimmy) • gg→WW →μμ(gg2WW + jimmy) • bb→μμ(pythiaB) • Z➝μμγevent selection ✒ Cut A: select 2 muons per event (ETμ1> 20 GeV, ETμ2> 6 GeV) ✒ Cut B: cut A+ iso cut to muon (Et cone < 5 GeV) ✒ Cut C: cut B + 1 loose photon per event (ETγ> 10 GeV) ✒ Cut D: cut C+ ΔR cut (Min(ΔR(μ1,γ), ΔR(μ2,γ)) >0.2) where ΔR = √(Δφ2 + Δη2) ✒ Cut E: cut D+ Mass cut (81 < Mμμγ < 101GeV) Search for H → γ γ

  27. Kinematic Variables Photons frZ →μμγ, Photons frH → γγ (mH = 120 GeV/c2) Search for H → γ γ

  28. Shower Shape Variables Photons frZ →μμγ Photons frH → γγ (mH = 120 GeV/c2) Required 30 < ET < 40 GeV Fside • Photons from Z→ mmγhave identical • shower shape to photons from • H→ γγ. • These photons can be used to • measure photon efficiency in data. f0 Search for H → γ γ

  29. Efficiency ofγin Z➝μμγevents • Photon efficiency from Z→μμγshows consistent behavior with H→γγ • The photons in Z→μμγcan be used to measure photon efficiency. Cross-section = 1143 pb forZ→ μμ Efficiency of cut-based ID vs. ET Efficiency of H-Matrix vs. ET H→ γγ Z→μμγ H→ γγ Z→μμγ Search for H → γ γ

  30. Statistical Uncertainty • The expected statistical error versus luminosity for different ET bins. • This graph takes only into account the 1/√Nbehavior of the • statistical error in each bin √s = 10 TeV For 200 pb−1 2% for 10 < ET < 20 GeV, 3% for 20 < ET < 40 GeV, 4% for 40 < ET< 60 GeV. Search for H → γ γ

  31. Sources of Background Photons in pp➝Z➝ μμEvents 81< M < 101 GeV 85< M < 95 GeV Search for H → γ γ

  32. Contamination by Other Standard Model Processes • Integrated luminosity : 200pb-1 • Center of mass energy : √s = 10 TeV Mμμγ (GeV) Search for H → γ γ

  33. Extrapolation to other Samples, Different η distribution • The photon identification efficiency is dependent on η of the • photon. • ✒ The total efficiency will not be correct if the photon efficiency derived from thephotons from Z→μμγis applied to samples with different ηdistribution. • To estimate the size of this effect, the photon efficiency is calculated • in a γ-jet sample in different η bins Search for H → γ γ

  34. PHOTON SHOWER IN ATLAS COSMIC-RAY MUON DATA

  35. Motivation • To understand actual detector and e/γ ID performance, we need to compare in data and simulation ✒ Low level calorimeter quantities (noise, resolutions, …) ✒ Intermediate level quantities (energy fractions, shower variables) ✒ High level (efficiency and rejection of electron/photon ID tools) • The ATLAS cosmic data from 2008 contain O(108) events • Large sample of EM showers in ATLAS cosmic data ✒ The high-energy bremsstrahlungphotons produced from cosmic muons ✒ Actual shower distribution in data • Unlike photon from collision, photon from cosmic-ray muon has different energy profile in each layer of EM calorimeter ✒ Shower shape distribution may differ ✒ Study shower shape with place where photon emitted from cosmic muon. Search for H → γ γ

  36. Photon Emission Point (i) • Find photon emission point from muon in cosmic ✒ Photon shower variables are sensitive depending on where photon radiated from muon track ✒ Track parameters of muon & positions of EM shower in the1st and 2nd layers ✒ The interception point of muon track and photon trajectory • Xγ and Yγ : the transverse coordinates of the emission points of the photons from μ→μγ • Rγ = √Xγ2 + Yγ2 ✒ equivalent to the true value of μ → μγvertex radius Rvertex Rγ =√Xγ2 + Yγ2 Search for H → γ γ

  37. Photon Emission Point (ii) • The most probable value for Rγ corresponds to middle of EM • Photon have less probability to be recognized as photon if the shower occurs in different region of ATLAS Rγ -Rvertex Search for H → γ γ

  38. Cosmic Data and Simulation • Data: Triggered by L1Calo and IDCosmic data streams ✒ merged two data stream with removing double counted events • Cosmic simulation : produced with inner detector volume Cut Flow Search for H → γ γ

  39. Comparison of Kinematic Variables • Kinematic variables of photon in MC & data have good agreement. • Impact parameter d0 of muon shows difference in MC & data ✒ It could be the differences of trigger & tracking efficiencies in MC & data Search for H → γ γ

  40. Shower Shape Comparison • Longitudinal shower variables • Most distributions of shower • variables are in agreement • between data & MC • Data is well modeled by • simulation. • Z→ μμγallows to do similar studies in collision data with much higher precision Search for H → γ γ

  41. PROSPECT FOR HIGGS SEARCH USING H ➝ 

  42. Signal and Background Process • Signal process (√s = 10 TeV) ✒ Gluon fusion process : masses of Higgs are 115, 120, 130, and 140 GeV/c2 • Background processes (√s = 10 TeV ) ✒ Irreducible background • Two prompt photons from qq→γγor gg→γγq • Bremsstrahlung from qg→qγ→qγγ . ✒ Reducible background a. γ-jet events where a leading π0 in a jet has been misidentified as one photon b. jet-jet events where both jets have been misidentified as photons. • Signal selection ✒ η cuts : |η| < 1.37 or 1.52 < |η| < 2. 37 (remove crack regions) ✒ pT cut on photons : pTγ1 > 40 GeV, pTγ2> 25 GeV Search for H → γ γ

  43. Kinematic Variables Subleading photon Leading photon √s = 10 TeV √s = 10 TeV H ➝γγ(mH = 140 GeV/c2) H ➝γγ(mH = 120 GeV/c2) Search for H → γ γ

  44. Signal Significance • Signal significance : expected number of signal and background events. • Requiring event preselection, mass cut mH ± 1.4σ and H-matrix cut. • Using the fake rates and efficiency for different χ2 cut values the expected number of photon events at 100 fb−1 and √s = 10 TeV are obtained. Search for H → γ γ

  45. Conclusions (i) • A covariant matrix based algorithm has been developed to identify electrons and photons. ✒ Exploits the high granularity of the ATLAS EM calorimeter and use correlations between various EM shower shape variables ✒ To enhance further the jet rejection a jet H-matrix has been built and combined with the photon H-matrix. ✒ The electron H-matrix shows significantly better performance than the current standard ATLAS cut-based electron. ✒ The combined photon-jet H-matrix shows also excellent jet rejection but is comparable to the ATLAS cut-based method • Prior to the LHC beam, considerable amount of cosmic data were collected with the ATLAS detector ✒ Provided a great opportunity to study the detector response and compare it to the predictions of the simulation ✒ The shower shapes of photon in the cosmic-ray data and simulation are in good agreement. ✒ The shower shape variables produced by the geantsimulation can be relied on. Search for H → γ γ

  46. Conclusions (ii) • A new process has been studied that will allow to measure the photon identification efficiency directly with the atlas data. ✒ Using bremsstrahlung photons in Z → μμγevents a pure sample of prompt photons can be isolated. ✒ It is possible to precisely extract efficiencies for photons with ET below 40 GeV • H → γγis very challenging and will only be possible to discover this signal once the atlas and the lhchave reached their design performance. ✒ The photon H-matrix provides a powerful tool to reject the γ +jet and jet-jet backgrounds to the H → γγsignal. • The validation of the photon H-matrix should become possible in data with the Z → μμγevents well before the search for H → γγbecomes statistically competitive. • With the upcoming atlas data it will soon be possible to measure the photon identification performance in real data (Now ready for data in Higgs search) Search for H → γ γ

  47. Backup

  48. +35 MH = 85 GeV/c2 -27 The Latest Result From Tevatron • The LEP EW working group has combined the experimental data from several precision EW measurements of SM parameters. ✒ the LEP experiment has set a 95% confidence level (CL) limit on the Higgs mass: mH> 114.4 GeV @ 95% CL. Search for H → γ γ

  49. g p p H g H➝  channel • Very rare decay (BR ~10-3) • Background ✒ Irreducible:  continuum ✒ Reducible: -jet and jet-jet • Keys ✒ Excellent energy and angular resolutions, ✒ Excellent  efficiency, jet rejection ✒ High granularity and response uniformity ✒ H width negligible, resolution dominated by detector ✒ σ(M)/M Search for H → γ γ

  50. ATLAS Coordinate System • The ATLAS Coordinate System is a right-handed system • The x-axis pointing to the centre of the LHC ring, the z-axis following the beam direction and the y-axis going upwards. ✒ At ATLAS positive z points towards LHCb. ✒ The azimuthal angle φ = 0 corresponds to the positive x-axis and φincreases clock-wise looking into the positive z direction. ✒ The polar angle θ is measured from the positive z axis. Search for H → γ γ

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