Top into Dileptons Dileptons Top into Stano Tokar Comenius - PowerPoint PPT Presentation

RTN Workshop Barcelona 18-20 Dec 2004 Top into Dileptons Dileptons Top into Stano Tokar Comenius University, Bratislava With a kind permissison of the CDF top group Stano Tokar, slide 1

Talk Outline Talk Outline • Top quark is treated in Dilepton mode • Main subjects: t t ⇒ production cross section (Details in: CDF6588, c.f. also CDF6517,-79,-90,-91,92) ⇒ Top quark mass reconstruction (Details in: CDF-6465) www-cdf.fnal.gov/internal/physics/top/run2dil/summer03/doc.html) Stano Tokar, slide 2

Top Dilepton Dilepton Characteristics Characteristics Top • Top dilepton topology: ( )( ) ( )( ) + − + − → + → → ν ν � p p tt X , tt W b W b l b l b tt • Branching ratio: 2/9 × 2/9 ≈ 4.9 % of all events • Characteristics of top dilepton mode – Two high P T opposite charge leptons – High missing E T (due to neutrinos) – Two high P T b -jets • Advatages: Very clean events sample. tt • Disadvantages: low branching ratio Stano Tokar, slide 3

Top Dilepton Dilepton Selection criteria Selection criteria Top Top dilepton event selection cuts: Run I vs Run II Cut Run I Run II (Winter 2003) Two ≥ 20 GeV opposite Two ≥ 20 GeV isolated 1 signed leptons, ≥ 1 isolated leptons 2 Remove Z bosons Remove Z bosons 76<M <106 GeV 76<M <106 GeV ee,µµ ee,µµ 3 / T E >25 GeV E >25 GeV / T ( ) ( ) / / ∆φ E , nearest l or j >20° ∆φ E , nearest l or j >20° 4 T T if E <50 GeV / if E <50 GeV / T T E / raw >10 GeV E / raw >10 GeV ≥ 2 jets with 5 2 jets with T T | η detector |< 2.0 | η detector |< 2.0 6 H T > 200 GeV 7 Opposite charge requirement ∑ ∑ = + / + tight leptons pass jets . (motivation: CDF5676) H E E E T T T T Stano Tokar, slide 4

Cross section Cross section • Run II status (Summer’03) = s 1 96TeV . ⇒ CMS energy: ∫ L ฀ 126 pb − ⋅ = 1 dt ⇒ Integrated luminosity: • Cross section: ( ) ⋅ ∫ L σ = − ⋅ ε N N A dt obs bg N obs ≡ # of events observed N bg ≡ # of estimated background events A ≡ Kinematic and geometrical acceptance ε ≡ Total efficiency • Winter’03 selection criteria modified: Only one isolated lepton required Plug electrons and CMIO muons included Z mass window cut replaced by a special procedure Stano Tokar, slide 5

X- -section: Event Selection, section: Event Selection, ∆φ ∆φ , H , H T X T… … Cuts in ( ∆φ , missing E T )-plane: Cut in H T : Data vs MC Signal MC vs data (ee, µµ , e µ ) and BKGD( DY, WW/WZ, Z →ττ , fake leptons) Stano Tokar, slide 6

X- -section: Event Selection section: Event Selection - - miss miss- -E E T , P T X T , P T Cut in miss-E T (>25 GeV): Cut in lepton P T (>20 GEV): Data vs MC Signal and BKGD( DY, Data vs MC Signal and BKGD( DY, WW/WZ, Z →ττ , fake leptons) WW/WZ, Z →ττ , fake leptons) Stano Tokar, slide 7

X- -section: # of jets, section: # of jets, dilepton dilepton mass mass X / E # of jets in dilepton + events Dilepton invariant mass: T vs MC signal and background Data vs MC signal and bkgd Stano Tokar, slide 8

Cross-section A good agreement with others and theory! Stano Tokar, slide 9

Top Mass in the Dilepton Dilepton Channel Channel Top Mass in the Summary of the top mass reconstruction method: – Kinematic reconstruction of events selected by the dilepton selection criteria – 24 parameters looked for at 23 constraints + assumption on the P distribution introduced t t z , – MC templates employed in exper. data and bkgd analyses ( ) = inp inp f m , m , m 140 150 , , � , 210 t rec , t t – Top mass is obtained using likelihood fit with the likelihood function defined: n = ∏ ( ) ( ) i inp L f m , m n ≡ # of events passed the selection t rec , t = i 1 criteria Stano Tokar, slide 10

Top Candidates in Dilepton Dilepton Mode Mode Top Candidates in Run I selected top candidates, ( ) ∆φ E , cut carried out in plane T ∆φ ≡ angle(MET, lepton (jet) direction) Sample: 109 pb -1 Run II selected top candidates, ( ) ∆φ cut carried out in plane E , T Sample: 126 pb -1 6 top dilepton candidates found Winter’03 selection criteria applied! Stano Tokar, slide 11

Masses of Top Candidates in Dilepton Dilepton Mode Mode Masses of Top Candidates in Only 6 events (vs 10 in xsec) due to more stringent criteria Stano Tokar, slide 12

MC Signal Templates MC Signal Templates tt • Samples of events produced (Pythia) for different input top masses: ( ) = inp 2 m 140 150 , , … . 210 GeV c / t • Simulated events are reconstructed (top dilepton selection criteria applied) and template − normalized distribution of (reconstructed rec m t inp top mass) − is found and fitted for each m t • Template parametrization ⇒ a combination of Landau-like distribution and Gaussian: ( ) inp p m ( ) ( ) 3 t = − λ + − λ rec inp f m ( , m ) exp 0 5 . exp( ) t t I 1 ( ) ( ) − inp 1 p m ( ) 3 t + − λ 2 exp 0 5 . I 2 ( ) rec − inp m p m ( ) t 1 t λ = = + ⋅ inp inp p m a b m ( ) i t i i t inp p m 2 t Stano Tokar, slide 13

Signal MC templates Signal MC templates p i parametrization • a b p 1 22.57 0.8 ± 0.017 ± 2.82 p 2 -21.35 0.26 ± 0.017 ± 2.3 p 3 1.0 - .0036 ± 0.16 ± .0003 • From = + × inp p a b m i i i t ⇒ Signal template ( ) rec inp f m , m s t t inp m is known for any t Stano Tokar, slide 14

Background Templates Background Templates Bkgd templates have the same form as the signal ones, but inp m p i do not depend on t Bkgd p 1 p 2 p 3 WW 143.0 ± 1.83 21.93 ± 1.59 0.63 ± 0.095 Z 0 →ττ 150.5 ± 3.11 26.37 ± 3.01 0.86 ± 0.13 Drell-Yan 167.2 ± 11.9 32.28 ± 9.4 1.19 ± 0.31 Stano Tokar, slide 15

Templates & Top Quark Mass Templates & Top Quark Mass ⇒ Pseudo-experiments with 6 random events repeated for each of 8 input top masses ⇒ 6 top masses resulted from each pseudo-experiment are put into likelihood fit: n ( ) ∏  = ⋅ rec L b f m  b t i , = i 1 ( )  + − ⋅ rec ( 1 b ) f m , m  s t i , t ⇒ top mass m t & its error are got from the likelihood fit Mean values of top masses ( ⇑ ) And their errors ( ⇐ ) Stano Tokar, slide 16

Pseudo- -experiment Results experiment Results Pseudo 6 events pseudo-experiments a b c with different input top masses (160, 170, 180 and 190 GeV) 1 1 2 3 4 have been carried out. 2 Each pseudo-experiment gives 6 ”raw” top masses – from them 3 Likelihood fit finds: a) top mass b) its error =m fit − m inp c) pull ( ) 4 t t ⇑ Distributions of top masses, errors and pulls from likelihood fits Stano Tokar, slide 17

Dilepton Top Quark Mass Top Quark Mass Dilepton Top mass is obtained from data using likelihood fit − likelihood function is known for any top mass (at least for (140, 210) GeV): n ( ) ( ) ∏   = ⋅ + − ⋅ rec rec L b f m ( 1 b ) f m , M b ≡ bkgd percentage =   b t i , s t i , top i 1 Applied to 6 experimental events ⇒ Stano Tokar, slide 18

Background Background Background expectation at 126 pb- 1 Probability of finding in 6 dilepton events : Bkgd Exp. # of events • no background is 59.5 % • 1 bkgd event – 32.3 % WW/WZ 0.165 ± 0.132 • 2 bkgd events – 7.3 % Drell-Yan 0.173 ± 0.121 Uncertainty ∆ m t ≈ 1.2 ± 0.2 GeV is obtained from likelihood fit assuming Z →ττ 0.165 ± 0.069 different sole background contributions. Fake 0.065 ± 0.052 Systematics ≈ 0.2 GeV comes from 1 σ variation of individual bkgd templates Total 0.52 ± 0.20 Bkgd expectation values are scaled from those at 72 pb -1 (CDFNOTE 6319) Stano Tokar, slide 19

Dilepton Top Mass Top Mass Systematics Systematics Dilepton Mass determination is sensitive to MC templates , jet reconstruction • Jet energy systematics: Sample of events (Pythia) at m t =170 GeV generated, tt sets of events for each jet correction created and reconstructed, pseudo-experiments with 5 events carried out, ± 1σ deviation applied for each jet correction. • Generator systematics: 2 PDF sets used: CTEQ5L and MRST Pythia vs Herwig ISR and FSR taken from Run I Stano Tokar, slide 20

Dilepton Top Mass Top Mass Dilepton • Top mass determined in the dilepton mode ⇒ the experimental sample of 126 pb -1 processed ⇒ the winter conference top dilepton selection criteria applied +17.4 2 M =175. 0 (stat)±7.9(syst) GeV c top -16.9 Stano Tokar, slide 21