Sensitivity Study on Top Quark Pair Resonance Search Tatsuma Meguro University of Tsukuba

motivation The large mass of top quark could be sensitive to the physics beyond the standard model. Many theories predict new particles preferentially coupled to the 3rd family, in particular top quark Model independent search is desirable.

Motivation 2 Current interest is in the high mass tail region (signal model can be anything) There are few background in the interested region (700~1000GeV) . We can’t tell whether there is interference effect or not because of small data size. Analysis is a little bit simpler without interference case. increase the signal acceptance include pretag events [~100%: assuming tag/jet=30% at high mass region] include >=5jet events [~30%] (jet assignment become difficult) include more lepton category [~20%] (don’t need not-good quality lepton with very high pt) Separate events into different sensitivity categories By tagging information

Event Selection (standard selection)

ttbar invariant mass reconstruction

Background <The background estimation> Use Official MC sample of each process from Method 2 table <The background estimation> 1,Apply MDL for each MC sample 2,Calculate Acc.*Xs*Br and merge samples in this ratio 3,Normalize according to method 2 table 4,we can get background shape (ex: pretag LF background(below) ) Ex) Pretag LF background 0 parton + W(->e nu) 1 parton + W(->e nu) 2 parton + W(->e nu) 3 parton + W(->e nu) 4 parton + W(->e nu) 0 parton + W(->mu nu) 1 parton + W(->mu nu) 2 parton + W(->mu nu) 3 parton + W(->mu nu) 4 parton + W(->mu nu)

Signal template Signal : Z' -> ttbar (width=1 GeV) Old sample odd tail in low mass region. I guess this comes from p.d.f distribution. 1000GeV Neve black:Hepg red:Reconstructed 1200GeV sqrt(s)

ttbar invariant mass distribution taddeg sample pretag sample mass(GeV) mass(GeV)

rough estimation <Significance(pretag)/Significance(tag)> How to estimate: 1. Count events in each Z mass window. 2. Calculate significance = S/sqrt(B) pretag , tagged events separately. 3. Take ratio to see how much sensitivity improve by adding pretag events. Low mass region ~ 30% High mass region ~ 40% !! Z' mass (GeV)

Likelihood Fit G:Gaussian Signal : qqbar -> Z' -> ttbar Background : others(10~11 shapes) mu : Number of expectation in i th bin (= Nbkg + Nsig(Xs x Br x Lumi. x Acc.) ) ni : Number of pseudo data in i th bin G(Nbkg,) for background constrain G(Nsig,) for signal systematics 95%CL Likelihood Cross section We can retrieve 95% C.L. upper limit from L(x) plot

How To Set Limit Templete hMtt_ttop75 hMtt_zpr500 95%CL distribution 1, Make distribution from Pseudo experiment (w/o Z' event , Ndata = 500 ) hMtt_ttop75 hMtt_zpr500 GeV normalized BG(left) , signal(right) distribution 95%CL distribution 2,Calculate the likelihood for Xs of Z' and set 95%C.L upper limit we can get one point from 1-pseudo experiment 95%CL Likelihood Cross section

Expected 95% C.L upper limit Mz' = 400GeV Mz' = 500GeV 95% upper limit cross section cross section (Z’)BR(Z’ttbar) Mz' = 600GeV Mz' = 700GeV cross section cross section Mz' Mz' = 800GeV Mz' = 900GeV cross section cross section

Estimation of systematic uncertainty(JES) top mass PDF LO/NLO hadronization(generator) ISR/FSR b-tag Efficiency black:default red:JES + sigma_JES blue:JES - sigma_JES Mttbar Mttbar Suppose JES is dominant, I used only the uncertainty from JES in this analysis. Apply to G(Nbkg,sigma_bkg)

summary made Signal MC reconstruct ttbar inbariant mass (signal and background) estimate 95% upper limit Z' cross section for each mass region , pretag ,tag event separately. Add pretag events to see how much improve the sensitivity... XX% Improvement in low mass region (500GeV) XX% Improvement in high mass region (1000GeV) Other models will indicate same trend for sensitivity search

backup

rough estimate Sensitivity = Signal/sqrt(Background) Total pretag events : 851 Total tagged events : 371 (from method 2 table) pretag : Nsig / sqrt(851) ~ N*0.6 / 29.17 tagged : Nsig' / sqrt(371) ~ N*0.4 / 19.26 -> about 40% improvement in rough estimate!!

signal template 350(GeV) 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 Neve red:Ntag=0 blue:Ntag>1 sqrt(s)

Identical Matched Jet (Old sample) 2876 2074 2933 2061 3029 2205 3172 2336 3180 2427 3374 2440 3314 2493 3126 2385 3169 2363 3046 2346 3010 2307 2993 2201 2900 2065 2559 1984 2635 2059 2515 1964 2492 1941 2606 1964 Red Identical Jet Blue Not Identical Reconstructed (Hepg-Rec)/Hepg These plots are normalized

Problem of Pythia influence from p.d.f ? So, I am planning to make new Z' template (Z' width = 1 GeV) default width width = 1 Gev number of event sqrt(shat) GeV