zhh channel: software and detector performances for ilc
DESCRIPTION
ZHH channel: software and detector performances for ILC. Michele Faucci Giannelli Fabrizio Salvatore Mike Green, Tao Wu. OUTLINE. This is an update to the LC note LC-PHSM-2007-003. ZHH Channel: summary of reconstruction and software used Generator differences Tracking performances - PowerPoint PPT PresentationTRANSCRIPT
ZHH channel: software and detector performances for ILC
Michele Faucci GiannelliFabrizio Salvatore
Mike Green, Tao Wu
07/02/2007 Michele Faucci Giannelli 2
OUTLINE
• ZHH Channel: summary of reconstruction and software used
• Generator differences
• Tracking performances
• Particle Flow Algorithm performances
• Detector comparison
• First look at background
• Conclusions
This is an update to the LC note LC-PHSM-2007-003
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ZHH Channel• The e+e-→ZHH channel is an excellent
benchmark for many steps of the simulation:– Different generators give different cross sections– Test physics lists available in detector simulation– Requires high performances from all detectors
• Vertexing• Tracking• Clustering
– Thus can be used to test particle flow algorithms– Finally can be used to compare different detector
models
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Generation and Simulation
• Events have been generated using Pandora-Pythia and Whizard
• The reconstruction was performed by Mokka (V06-03p02):– Some information @ generation level:
• ECM = 500 GeV• M(Higgs) = 120 GeV/c2
• Polarized 80% electron beam• Two detector model (LDC00Sc and
LDC01Sc)• Z→l+l- (muons and electrons)
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Marlin Processors
Marlin 0.9.7 + MarlinReco 0.3– Processors used:
• VTXDigi• FTDDigi• TPCDigi• Tracking Processors• PFA Processors• PairSelector• SatoruJetFinder• BosonSelector• MyROOTProcessor
Tracking Processors:– FullLDC:
• LEPTrackingProcessor• SiliconTracking• FullLDCTrackin
– TrackCheater
PFA Processors:– Wolf:
• TrackWiseClustering• Wolf• ClusterMerge
– PandoraPFA:– TrackBasedPFA:
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ZHH selection• Select and extract the two leptons which better
reconstruct the Z.• Combine all the other particles in 4 jets.
– Reconstruct the two Higgs minimizing the quantity:
• Look at different variables to compare the two available PFA algorithms:– D2 and other combinations of jet-jet inv. Mass
• The mass of the Higgs used in the analysis is 114 GeV instead of 120 GeV to take into account the effect of invisible particles
2h342
h122hh mmmmD
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WOLF
Invisible particles
Black: normal reconstructionRed: with neutrinos
On average, contribution from ‘invisible particles’ ~ 6 GeV
Adding this contribution, reconstructed H mass with Wolf higher than mH value used in the
generation. LDC01Sc
PANDORA
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GeneratorsTree generators:– Pandora Pythia– Pandora Phytia with K, , , NOT decayed– Whizard
No visible
difference noticed
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TrackingTwo Tracking algorithms:– FullLDC Tracking– TrackCheater
No visible
difference noticed
Tracking is good enough
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PFA ComparisonThree PFA available:– PandoraPFA– Wolf– TrackbasedPFA
Z→ee
Problem in TrackbasedPFA with particle identification
Cut on Z mass in the Higgs Plot to select good events
Z→mm
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Higgs Mass
Z→ee
Z→Pandora has a very good RMS for muons, probably too low mean
Wolf reconstructs too high mass Higgs
The problem with muon id affects the Higgs reconstruction in TrackbasedPFA
Pandora has some problem with electron id, high energy tail (bremsstrahlung?)
Wolf reconstructs too high mass Higgs
TrackbasedPFA has a very good performance with electrons! Algorithm works!!
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Higgs discrimination: D plot• D is defined as h3412hh mmmD *2
For muons PandoraPFA is the best algorithm
For electrons Pandora and TrackbasedPFA are comparable
Z→ee
Z→
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Higgs discrimination: D2 plot 2h34
2h12
2hh mmmmD • D2 is defined as
Z→ee
Z→
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Detector comparison
LDC00SCLDC01Sc
No differences in the muon case
LDC01Sc is better than LDC00Sc for electron, less material then less bremsstrahlung?
Z→ee
Z→ PandoraPFA
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First look at Background(I)
Z→ee
ZHHZZHZZZ
TrackbasedPFA
PandoraPFA
Pandora is better not only for a more efficient signal reconstruction but for a smaller contamination too
LDC00Sc
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First look at Background (II)
Z→ee
Z→
ZHHZZHZZZ
PandoraPFA
Good discrimination for muons, a factor 2 better than electrons.
ParticleID has a crucial role, more effort are needed!
LDC00Sc
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First look at Background (III)
ZHHZZHZZZ
PandoraPFALDC00Sc
Same as previous slide, linear scale
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Conclusion• Comparison between generators:
– No visible differences between generators
• Comparison between tracking:– FullLDC is as good as cheater for our analysis
• Comparison between PFA: – Trackbased almost as good as Pandora, both need
a better Particle ID.
• Comparison of LDC00/01Sc using PandoraPFA– Small differences once electron ID is solved, both
detector models can be used to reconstruct this channel
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Conclusion• Studies on SM backgrounds
– ZZH and ZZZ have been simulated and reconstructed:
it is possible to discriminate the signal!!
• Future Plans– Study high cross section channels
• Understand how to apply cut at generation level to reduce the amount of events to simulate in Mokka
– Move to 6 jets analysis• B tagging is necessary• Looking at a new strategy for Z selection
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Backup slides
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Preparation: calibration
• Check calibration for pions and electrons
Black PandoraRed Wolf
LDC01Sc
Pions
Electrons
GeV
GeV