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

2. 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.

3. 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

4. Event Selection (standard selection)

5. ttbar invariant mass reconstruction

6. 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)

7. 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)

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

9. 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)

10. 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

11. 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

12. 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

13. 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)

14. 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

15. backup

16. 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!!

17. signal template
350(GeV)
Neve
red:Ntag=0
blue:Ntag>1
sqrt(s)

18. 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

19. 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