1. Effect of t42 algorithm on jets
Emmanuel Busato
LPNHE Paris
Noise jets suppression with t42
Effect of t42 on real jets
 Jet quality cuts efficiencies
 Energy lost by good jets
 Reconstruction efficiency in Monte Carlo
 Resolution in Monte Carlo

2. 1. Noise jets suppression with t42
Data sample :
alljets skim from top group = 4JT10 + 4JCCB + HT>100
Color code : t no t42
Number of jets/event
Big difference

3. t42 and new seeding go in the same direction remove fake jets
Effect of new seeding
Jets found in both cases
Jets not found with new seeding
mean = 0.43
mean = 2.22
Effect of t42 algorithm
t42 and new seeding go in the same direction
remove fake jets

4. 2. Effect of t42 on real jets Jet quality cuts efficiencies
Data sample :
 stripped thumbnails of jet-photon events from JES :
 reco version : p
 triggers : all single electromagnetic triggers in CMT-9.50
 At least one EM object with |id|=10,11 and pT > 4.0 GeV
Additional cuts :
 Photon candidate selection :
 Hmx8<20
 Isolation<0.15
 EM fraction>0.9
 in fiducial
 no track match
  (jet-photon)>3.0
Method : use photonjet events, apply back to back requirement to maximize real jets over fakes  apply quality cuts on these jets

5. Jets properties
t no t42
EMF
CHF
f90
n90

6. Efficiencies for each cut individually
Total   0.008
(Statistical error only)
 Higher efficiency with t42
 Quality cuts may be reconsidered

7. Energy lost by good jets the same jet is less energetic with t42
Data (alljets skim from top group)
 735 MeV
difference for
the same jet
 need new JES correction
MC (single top events) :
with noise
without noise
 t42 cuts real energy

8. Reconstruction efficiency in MC (qcd pT20)
Method : match particle jets to calorimeter jets with R 0.5
reco efficiency = pT particle jets found in calo / pT all particle jets
 Efficiency lower with t42 when pTjet  8 GeV.
Gain a lot of efficiency by lowering the threshold to 6 GeV
What about noise jets with this new threshold ?

9. Data
(alljets skim)
New low pT good jets
(reco efficiency higher).
New jets found with [t42, pTjet  6 GeV] in second bump may also be
low pT good jets.
Even if they are fake, situation better than in the [not42, pTjet  8 GeV] case.

10. Energy resolution in MC (qcd pT20)
Method : match particle jets to calorimeter jets with R 0.5
 E / E = (E particle jets – E cal jets ) / E particle jet distribution in several pT bin
Fit with a gaussian in each pT bin.

11. Result
resolution better at low energy
better fit after t42

12. Conclusion
t42 algorithm allows to cut out fake jets without degrading real
jets reconstruction.
We propose to set it in killing mode in the reconstruction in p