Lighting up the Higgs sector with photons at CDF Baylor HEP Seminar Karen Bland November 12, 2011
Download ReportTranscript Lighting up the Higgs sector with photons at CDF Baylor HEP Seminar Karen Bland November 12, 2011
Lighting up the Higgs sector with photons at CDF Baylor HEP Seminar Karen Bland November 12, 2011 1 Outline • Introduction • Tevatron and CDF Detector • Photon ID and Efficiency • SM Hγγ Search • Fermiophobic hγγ Search • Summary and Conclusions 2 Outline • Introduction – Theoretical Overview – Motivation • Tevatron and CDF Detector • Photon ID and Efficiency • SM Hγγ Search • Fermiophobic hγγ Search • Summary and Conclusions 3 The Standard Model • Higgs boson is only SM particle that hasn’t been observed! • Through the Higgs mechanism: (1) Electroweak symmetry is broken (2) Other SM particles acquire mass • But mass of Higgs boson a free parameter… • Has to be determined experimentally if exists • What we know so far: • Lower mass SM Higgs boson mass preferred by electroweak constraints • Search focus: mH =114 – 145 GeV • SM Higgs boson not to be discovered at Tevatron • However through spring 2012 Tevatron, more sensitive in much of search region than LHC experiments 4 The Standard Model • Higgs boson is only SM particle that hasn’t been observed! • Through the Higgs mechanism: (1) Electroweak symmetry is broken (2) Other SM particles acquire mass • But mass of Higgs boson a free parameter… • Has to be determined experimentally if exists • What we know so far: Hγγ contributes sensitivity here • Lower mass SM Higgs boson mass preferred Tevatron experiments are by electroweak stillconstraints working very hard to improve analysis • Search focus: mH =114 and – 145 GeV techniques add final •datasets SM Higgs not to to fillboson in as much ofbe thediscovered remainingatgaps as Tevatron possible. • However through spring 2012 Tevatron, The Hsensitive γγ analysis more in much of search region than contributes to this effort LHC experiments 5 SM Higgs Production at the Tevatron Gluon Fusion • ggH is largest cross section • Excluded from channels where Higgs decays to quarks due to multijet backgrounds (like Hbb) Associated Production Vector Boson Fusion 6 SM Higgs Production at the Tevatron Gluon Fusion ~ 1000 fb @ 120 GeV is largest cross section •• ggH Produced only rarely: Excluded from channels where Higgs ◦ One out ofdue every 10 collisions decays to quarks to multijet backgrounds Hbb) ◦ That’s (like about 2 Higgs bosons eachallweek • Hγγproduced gains by using three production methods (~1300 fb) 12 Associated Production ~ 225 fb @ 120 GeV Vector Boson Fusion ~ 70 fb @ 120 GeV 7 SM Hγγ Decay • Dominant low mass decay mode is Hbb • Hγγ Br < 0.25% • Signal expectation @ 120 GeV: N = σ × L × Br = 1300fb × 7.0fb-1 × 0.002 ~ 18 Hγγ events produced (~ 6 reconstructed) 8 Is a Hγγ search interesting at the Tevatron? • Small Br, however contributes sensitivity to Tevatron search in difficult region ~125 GeV: • Many beyond SM scenarios include a larger Br(Hγγ) • New results for one such scenario shown later in the talk 9 Is a Hγγ search interesting at the Tevatron? • Clean signature compared to Hbb – Photons (or electrons from photon conversions) easier to identify/reconstruct than b-jets – Larger fraction of Hγγ events accepted in comparison – Total acceptance: • ~35% accepted for ggH • ~30% accepted for VH and VBF – Largest efficiency losses from fiducial requirements and ID efficiency – Also improves reconstructed mass resolution… 10 Is a Hγγ search interesting at the Tevatron? • Great mass resolution: – Mass resolution limited only by electromagnetic (EM) calorimeter and ability to select correct vertex of event (natural width negligible) – 1σ width ~3 GeV or less (Mjj width is ~16 GeV) – Resolution ~5x better than best jet algorithms for Hbb 2.5% – Great background M discrimination using Mγγ alone – Search for narrow resonance on smoothly falling background – Fits to non-signal region of mass spectrum can be used to estimate background 11 Outline • Introduction • Tevatron and CDF Detector • Photon ID and Efficiency • SM Hγγ Search • Fermiophobic hγγ Search • Summary and Conclusions 12 Tevatron • pp collisions at √s = 1.96 TeV • Peak luminosity 414×1032 cm-2s-1 • Shut down on Sept. 30th, 2011 • 11.9 fb-1 delivered • 9.9 fb-1 stored on tape at CDF Results shown here use 7.0 fb-1 13 CDF Detector and Particle Identification e’s and γ’s interact in calorimetry via electromagnetic cascades (i.e. ionization and bremmstrahlung for e’s and photoelectric effect, Compton scattering, and pair production for γ’s) Hadrons interact in calorimetry via cascades of nuclear interactions (much more complex than EM cascades) “Jets” come from quarks or gluons fragmenting Muons long-lived and won’t interact in calorimetry; leave track in tracking detector and muon chambers Charged particles leave a “track” in the tracking chambers Want a detector that can differentiate between different types of final state particles 14 CDF Detector Electromagnetic Calorimeter Hadronic Calorimeter Central Tracker p p Muon Chambers Silicon Vertex Detector Solenoid Outline • Introduction • Tevatron and CDF Detector • Photon ID and Efficiency – – – – Introduction Central Photons Forward Photons Conversion Photons • SM Hγγ Search • Fermiophobic hγγ Search • Summary and Conclusions 16 Photon Identification • “Central” – |η|<1.1 • “Plug” Central Plug – 1.2<|η|<2.8 – Tracking efficiency lower than in central region – Easier to miss a track and reconstruct fake object as a photon – Higher backgrounds then for plug photons Cross sectional view of one detector quadrant 17 Photon Identification • Basic Photon Signature: – Compact EM cluster – Isolated – No high momentum track associated with cluster – Profile (lateral shower shape) consistent with that of a prompt photon Signal Inside jets • Unlike that of π0/η γγ decays (the largest background for prompt photons) • Hard to do this with calorimeters alone Background 18 Photon Identification • ΕΜ calorimeter segmentation: – Δη×Δϕ ~ 0.1×15° (|η|<1) – Not fine enough to fully reject π0/η jets • Shower max detector – ~6 radiation lengths into EM calorimeter – Finely segmented – Gives resolution to better reject π0/ηγγ – Αlso refines EM cluster position measurement to better match associated tracks Hadronic Calorimeter Electromagnetic Calorimeter Shower maximum detector Signal Background 19 Central Photon Identification • Three level selection • (1) Loose requirements – Fiducial in shower max detector – Ratio of hadronic to electromagnetic transverse energy (Had/EM) < 12.5% – Calorimeter isolation • (2) Track veto – Number tracks ≤ 1 – If 1, then pTtrk1 < 1 GeV • (3) Cut on NN Output – More details on next slides • I. ETTot (R 0.4) ETEM • Cut slides with ETEM – Track isolation pTtrk < 5 GeV 0.4 trk|zR 0 ztrk | 5cm 20 Central Electron Identification • Three level selection • (1) Loose requirements – Fiducial in shower max detector – Ratio of hadronic to electromagnetic transverse energy (Had/EM) < 12.5% – Calorimeter isolation • I. ETTot (R 0.4) ETEM • Cut slides with ETEM – Track isolation pTtrk – pTtrk1 < 5 GeV 0.4 trk|zR 0 ztrk | 5cm • (2) Track veto – Number tracks ≤ 2 – If 2, then pTtrk2 < 1 GeV • (3) Cut on NN Output – More details on next slides • No pure high statistics data sample of photons to validate ID efficiency • Selection chosen so can be modified for electrons • Then use Ze+e– decays (more detail later) 21 Central Photon Identification NN discriminant constructed from seven well understood variables: – Ratio of hadronic to EM transverse energy – Shape in shower max compared to expectation – Calorimeter Isolation – Track isolation – Ratio of energy at shower max to total EM energy – Lateral sharing of energy between towers compared to expectation Trained using inclusive photon MC and jet MC (with ISR photons removed and energy reweighting) s/sqrt(b) for Hγγ vs NN cut gives optimum cut of 0.74 • Relative to standard photon selection, increases signal efficiency by 5% and background rejection by 12% 22 Central Photon ID Efficiency • ID efficiency checked in data and MC from Ze+e– decays • Z mass constraint applied to get a pure sample of electrons to probe • Effect of pile-up seen through Nvtx dependence • Net efficiencies obtained by folding εvtx into Nvtx distribution of diphoton data and signal MC (a weighted average) • Net photon ID efficiency: Data: 83.2% MC: 87.8% • MC scale factor of 94.8% applied • Total systematic uncertainty of 2% applied from: – Differences between electron vs photon response (checked in MC) – Data taking period dependence – Fits made to Z mass distribution • Small uncertainties using this method! 23 Plug Photon ID and Efficiency Standard CDF Cut-Based ID Same Efficiency Technique as for Central Photons • Fiducial in shower max detector • Ratio of hadronic to EM transverse energy* < 5% • Calorimeter isolation* < 2 GeV • Track isolation* < 2 GeV • Shape in shower max compared to expectation • Net photon ID efficiency: – Data: 73.2% – MC: 80.6% • MC scale factor of 90.7% applied • Total systematic uncertainty of 4.5% * Slides with EM energy or ET 24 Photon Conversions • γe+e– • Colinear tracks moving in approximately same direction • Occurs in presence of detector material • More material, higher the probability of converting port cards, cables L00, L0-L4 L6 ISL outer screen COT inner cylinder L7 25 Photon Conversions • Use central only • Then for two photons, % of events lost from a single central photon converting is: p ≈ 15% for central γ – 26% for CC channel – 15% for CP channel • CDF had only one Run I measurement using converted photons: γ cross section PRD,70, 074008 (2004) • Hγγ is the second analysis to use it for Run II • Conversion probability at CMS substantially higher*… ~70% of Hγγ events have at least one photon that converts!! Similarly for ATLAS Much more important at LHC experiments! • • • * J. Nysten, Nuclear Instruments and Methods in Physics Research A 534 (2004) 194-198 26 Conversion ID cut ~94% efficient • Base selection: – – – – |η|<1.1 Oppositely signed high quality tracks Proximity: r-fsep and Δcotθ e + (γ e+e–) “trident” veto photon radiated via bremmstrahlung • Other tighter selection on calorimeter and tracking variables applied to further reduce backgrounds • 7% uncertainty in conversion ID taken as systematic from Ze+trident studies r-ϕ separation (cm) cut ~95% efficient cotθ = pz/pT Example trident Δcotθ 27 Outline • Introduction • Photon ID and Efficiency • SM Hγγ Search – – – – Event Selection Background Modeling Results Tevatron Combination • Fermiophobic hγγ Search • Summary and Conclusions 28 Event Selection • Inclusive photon trigger – Single photon ET > 25 GeV – Trigger efficiency after offline selection obtained from trigger simulation assuming zvtx = 0 and trigger tower clustering • Use photon ID as previously described • Photon pT > 15 GeV • Four orthogonal diphoton categories: – Central-central photons (CC) – Central-plug photons (CP) – Central-central conversion photons (CC Conv) where one converts – Central-plug conversion photons (CP Conv) where central converts 29 Primary Background Composition • Real SM photons – Irreducible background – Via QCD processes from hard interaction • Fake backgrounds – Reducible backgrounds – Electrons from Z/γ*e+e– – Jets fragmenting to neutral mesons (π0/ηγγ) which then decay to pairs of colinear photons and are reconstructed as a single photons 30 Data-Driven Background Model • Fit to non-signal (“sideband”) regions of Mγγ distribution • We use a 6 parameter polynomial times exponential to model smooth portion of the data • Fit is then interpolated into the 12 GeV signal region to estimate background expectation for Higgs mass hypothesis • Example shown here for a test mass at 115 GeV for CC channel 31 Data-Driven Background Model • Channels with a plug photon have a non-neglible contaminated from Z background • Breit-Wigner function added to smooth distribution to model this, where mean and width are bounded in fit • Example shown here for a test mass at 115 GeV for CP channel 32 Background Model • Vertical red lines show window excluded from fit for Higgs mass hypothesis being tested • Interpolated fit used to obtain data-fit residuals • Used to inspect for signs of a resonance for each mass and channel • No significant resonance observed CC Channel CC Conversion Channel 33 Background Model • Vertical red lines show window excluded from fit for Higgs mass hypothesis being tested • Interpolated fit used to obtain data-fit residuals • Used to inspect for signs of a resonance for each mass and channel • No significant resonance observed CP Channel CP Conversion Channel 34 Background Rate Uncertainty • Parameters of fit function varied within uncertainties to obtain a new test fit • Integral in 12 GeV signal region calculated for test fit • Repeated many times • Largest upper and lower differences from standard fit stored • Then symmetrized to obtain rate uncertainty for each test mass and channel Approximate Systematic Errors on Background (%) CC 4 CP 1 CC Conv 8 CP Conv 4 • Model dependence checked by testing alternate fit functions • Variation in normalization as compared to standard found to be within uncertainties already obtained 35 CC Channel Discriminant and some Math Checks • • • • • • • • • • We show these distributions so you can check our results with some simple math… Use 12 GeV signal region, so as an example, here it would be 120 +- 6 GeV Real limits are much more complicated, but this is a rough check that results are in the right ball park • • N Signal (S) = 2.2, N Bkg (B) = 271 +- 16.5 16.5 1σ statistical error on the background expectation 68% of the time For S = 2.2, obviously we’re not sensitive to a SM Higgs observation How many signal events would we be sensitive to at say a 95% C.L? 33 2σ about 95% data fluctuates between 271 +- 33 The number 33 is simple 95% upper C.L. limit on the amount of reconstructed signal we’re sensitive to based on bkg expectation alone We can excludes models with predict > 33 γγ decays at this mass @ 95% C.L. How much is this relative to the SM prediction?: 33/2.2 = 15 This is a simple 95% C.L. upper limit relative to the SM prediction Including systematic uncertainties degrades limits by about 10-15% 36 Final Discriminants 37 Limits add as ~ 1/Li2 similar to a || resister, where Li is limit for an individual channel SM Limits • Shown are 95% upper C.L. limits on σ×Br relative to SM prediction using a Bayesian method • Most sensitive expected limit is for 120 GeV where limit is ~13.0×SM • An improvement of ~33% on last result presented! • Improvements from better central photon ID, including forward photons, and reconstructing photon conversions • Observed limit at ~28×SM above 2σ but we didn’t consider “lookelsewhere effect” • With this affect considered, has less than 2σ significance arXiv:1109.4427 To be published in PRL • This result included in Tevatron Higgs combination • First SM Higgs result from CDF Run II to be published • Has also been combined with D0 results to give a Tevatron SM Hγγ result… 38 DØ’s SM H→γγ Search • Uses a boosted decision tree as final Hγγ discriminant • Βased on five kinematic inputs: Mγγ, pTγγ, ET1, ET2, Δφγγ • Example output shown for mass of 115 GeV • • • • • From March 2011 Using 8.2fb-1 Observed @ 115: 12.5xSM Expected @ 115: 15.8xSM PRL 107, 151801 (2011) 39 Tevatron 95% C.L. Limits on Hγγ arXiv:1107.4960 For MH of 115 GeV Luminosity Expected/SM Observed/SM Tevatron Hγγ Combo ≤ 8.2 fb-1 8.5 10.5 40 Tevatron vs LHC • Due to higher jet backgrounds, the LHC is betting on the Hγγ channel rather than Hbb for a low mass Higgs discovery… • Also gain from higher cross sections, calorimeter resolution, and mass resolution • Limited by Br (as at Tevatron) and multiple interactions (pileup) • As of Sept, 2011 both CMS (CMS-PAS-HIG-11-021) and ATLAS (arXiv:1108.5895) have results in Hγγ of about 3-4xSM expectation: • Tevatron is clearly not competitive with LHC in this channel… how about in BSM models? 41 Outline • • • • • Introduction Tevatron and CDF Detector Photon ID and Efficiency SM Hγγ Search Fermiophobic hγγ Search – – – – Theory Motivation Differences in search from SM Results Tevatron Combination • Summary and Conclusions 42 Fermiophobic Higgs (hf) • It’s likely nature doesn’t follow the SM Higgs mechanism… • We also consider a “benchmark” fermiophobic model • A two-Higgs doublet model extension to the SM • Spontaneous symmetry breaking mechanism different for fermions and bosons 5 Higgs • We search for one in which: – No Higgs coupling to fermions – SM Higgs coupling to bosons – SM production cross sections assumed 43 Fermiophobic Higgs (hf) Production Gluon Fusion ~ 1000 fb @ 120 GeV No gghf σ ~ 300 fb @ 120 GeV Associated Production ~ 225 fb @ 120 GeV Vector Boson Fusion ~ 70 fb @ 120 GeV 44 Fermiophobic Higgs (hf) Decay • hbb no longer dominant Suppressed by m2b/m2W • Dominant low mass decay mode is now hγγ Br ~ 13x higher than SM @ 120 GeV • Signal expectation @ 120 GeV: N = σ × L × Br = 300fb × 7.0fb-1 × 0.03 ~63 (22) hfγγ events produced (reconstructed) ~4x higher than SM expectation 45 Fermiophobic Higgs (hf) Decay • hbb no longer dominant Suppressed by m2b/m2W • Dominant low mass decay mode is now hγγ Br ~ 120x higher than SM @ 100 GeV • Signal expectation @ 100 GeV: N = σ × L × Br = 560fb × 7.0fb-1 × 0.18 ~700 (245) hfγγ events produced (reconstructed) ~30x higher than SM expectation 46 Event Selection • Inclusive photon trigger – Single photon ET > 25 GeV – Trigger efficiency after offline selection obtained from trigger simulation assuming zvtx = 0 and trigger tower clustering • Use photon ID as previously described • Photon pT > 15 GeV • Four orthogonal diphoton categories: – Central-central photons (CC) – Central-plug photons (CP) – Central-central conversion photons (CC conv) where one converts – Central-plug conversion photons (CP conv) where central converts Same as SM Search Greatest sensitivity! • gghf suppressed • Optimize for VH/VBF • Split into three diphoton pt bins: – High: pT> 75 GeV – Medium: 35 < pT < 75 GeV – Low: pT < 35 GeV • 4 diphoton categories x 3 pT bins = 12 total channels Different for hf search 47 Background Model Example fits for CC for each pTγγ bin Same approach for background model as done for SM High pTγγ Bin Medium pTγγ Bin At 120 GeV: N signal = 2.9 s/sqrt(b) = 0.66 At 120 GeV: N signal = 2.5 s/sqrt(b) = 0.37 Low pTγγ Bin At 120 GeV: N signal = 1.3 s/sqrt(b) = 0.09 48 arXiv:1109.4427 To be published in PRL Results • At 95% C.L., observed (expected) on B(hfγγ) exclude a fermiophobic Higgs boson with a mass < 114 GeV (111 GeV) • A limit of 114 GeV is currently the world’s best limit on a hf Higgs from a single experiment • To be published in PRL with SM result Experiment • Has also been combined with D0 results to give a Tevatron hfγγ result… LEP Previous CDF PRL (3.0 fb-1) D0’s PRL result (8.2 fb-1) mhf limit (GeV) 109.7 106 112.9 CMS Prelim result (1.7 fb-1) 112 CDF new result (7.0 fb-1) 114 49 DØ’s fermiophobic hf→γγ Search • • • • Same as SM, but no ggH and higher Br Uses a boosted decision tree as final hfγγ discriminant Βased on five kinematic inputs: Mγγ, pTγγ, ET1, ET2, Δφγγ Example output shown for mass of 115 GeV • • • • • From March 2011 Using 8.2fb-1 Observed @ 115: 12.5xSM Expected @ 115: 15.8xSM PRL 107, 151801 (2011) 50 Tevatron 95% C.L. Limits on hf • This is what exclusion looks like • Tevatron results exclude fermiophobic Higgs bosons with masses below 119 GeV at 95% C.L. • This is the world’s best limit (arXiv:1109.0576) 51 Summary and Conclusions • CDF SM H and hf γγ soon to be published (we just got the bill) • Improvements at CDF upon previous analyses: – Inclusion of forward and conversion photons – Better central ID from a NN – Including lower pT regions to hf search • SM Hγγ search: – Not competitive with LHC, but contributes to final Higgs search at Tevatron – Tevatron Combination ~ 13xSM (observed) 9xSM (expected) • Fermiophobic hfγγ: – Tevatron setting world’s best limit on this model @ mhf > 119 GeV – CDF limit of 114 GeV most stringent limit by a single experiment • Both CDF analyses to be updated with full dataset and a few improvements, so stay tuned… 52 Backup 53 Stalking the Higgs Boson Indirect constraints • Precision electroweak observables are sensitive to the Higgs boson mass via quantum corrections. Direct searches at LEP • Tantalizing hints (~1.7) of a SM-like Higgs boson with mH~115 GeV: mH 9234 26 GeV Combining indirect and direct constraints mH< 161 GeV (95% CL) mH> 114.4 GeV (95% CL) 114.4 < mH< 161 GeV (95% CL) • Widths ~3 GeV (or less) for each channel Signal Shapes • Use 2σ width to determine signal window 12 GeV • Shapes used to fit for signal in the data when setting limits 55 Systematic Uncertainties on Hγγ Signal 56 Used two central photons from cut-based ID 12 GeV/c2 signal region for each test mass used to set upper limits set on σ Br relative to SM prediction Expected and observed limits in good agreement Expected limits of 19.4xSM @ 120 GeV Most sensitive for range 110 – 130 GeV/c2 Previous Limits on Hγγ at CDF using 5.4/fb Added to SM Higgs Tevatron combination this past summer 57 Fermiophobic Higgs (hf) • It’s likely nature doesn’t follow • 5 Physical Higgs Particles: h0, H0, A0, H+, and H– the SM Higgs mechanism… • We also consider a “benchmark” • 2HDM type-I – Scalar field mixing angle α fermiophobic model can lead to different couplings • A Two Higgs Doublet Model to fermions for h0 and H0 (2HDM) extension to SM: – sin(α) for H0 and cos(α) for h0 f1 f1 0 f1 – Limit of απ/2 yields a Higgs with enhanced coupling to bosons: h0hf f2 f2 0 f2 • With vacuum expectation values: • Standard model cross sections assumed 0 0 1 • Not present in MSSM f f 1 1 v1 2 Akeroyd, hep-ph/9511347, 1995 v 2 Introduction 58 Tight Conversion ID • Primary electron: – Fiducial – Had/EM < ~5.5% • Secondary electron: – Fiducial – pT > 1.0 GeV ~24% of events ~72% of events • Conversion photon – pT > 15 GeV – E/P ratio (optimized for Ηγγ) – Calorimeter isolation (optimized for Hγγ) – Rconv > 2.0 cm Photon ID and Efficiency – Conversion Photons 59 Conversion ID Efficiency • Search for “tridents” where one electron leg brems a photon which then converts • Probed conversions of lower momentum range than those from Hγγ • Obtain an uncertainty on conversion ID rather than MC scale factor • In data and MC calculate ratio: N(Z e trid) R N(Z ee) • Rdata/RMC 7% uncertainty Photon ID and Efficiency – Conversion Photons 60