ZHH channel: software and detector performances for ILC Michele Faucci Giannelli Fabrizio Salvatore Mike Green, Tao Wu.

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Presentation transcript:

ZHH channel: software and detector performances for ILC Michele Faucci Giannelli Fabrizio Salvatore Mike Green, Tao Wu

07/02/2007Michele Faucci Giannelli2 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

07/02/2007Michele Faucci Giannelli3 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

07/02/2007Michele Faucci Giannelli4 Generation and Simulation Events have been generated using Pandora-Pythia and Whizard The reconstruction was performed by Mokka (V06-03p02): –Some generation level: E CM = 500 GeV M(Higgs) = 120 GeV/c 2 Polarized 80% electron beam Two detector model (LDC00Sc and LDC01Sc) Z→ l + l - (muons and electrons)

07/02/2007Michele Faucci Giannelli5 Marlin Processors Marlin 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:

07/02/2007Michele Faucci Giannelli6 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: –D 2 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

07/02/2007Michele Faucci Giannelli7 WOLF Invisible particles Black: normal reconstruction Red: with neutrinos On average, contribution from ‘invisible particles’ ~ 6 GeV Adding this contribution, reconstructed H mass with Wolf higher than m H value used in the generation. LDC01Sc PANDORA

07/02/2007Michele Faucci Giannelli8 Generators Tree generators: –Pandora Pythia –Pandora Phytia with K, , – ,  NOT decayed –Whizard No visible difference noticed

07/02/2007Michele Faucci Giannelli9 Tracking Two Tracking algorithms: –FullLDC Tracking –TrackCheater No visible difference noticed Tracking is good enough

07/02/2007Michele Faucci Giannelli10 PFA Comparison Three 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

07/02/2007Michele Faucci Giannelli11 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!!

07/02/2007Michele Faucci Giannelli12 Higgs discrimination: D plot D is defined as For muons PandoraPFA is the best algorithm For electrons Pandora and TrackbasedPFA are comparable Z→ee Z→ 

07/02/2007Michele Faucci Giannelli13 Higgs discrimination: D 2 plot D 2 is defined as Z→ee Z→ 

07/02/2007Michele Faucci Giannelli14 Detector comparison LDC00SC LDC01Sc No differences in the muon case LDC01Sc is better than LDC00Sc for electron, less material then less bremsstrahlung? Z→ee Z→  PandoraPFA

07/02/2007Michele Faucci Giannelli15 First look at Background(I) Z→ee ZHH ZZH ZZZ TrackbasedPFA PandoraPFA Pandora is better not only for a more efficient signal reconstruction but for a smaller contamination too LDC00Sc

07/02/2007Michele Faucci Giannelli16 First look at Background (II) Z→ee Z→  ZHH ZZH ZZZ PandoraPFA Good discrimination for muons, a factor 2 better than electrons. ParticleID has a crucial role, more effort are needed! LDC00Sc

07/02/2007Michele Faucci Giannelli17 First look at Background (III) ZHH ZZH ZZZ PandoraPFA LDC00Sc Same as previous slide, linear scale

07/02/2007Michele Faucci Giannelli18 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

07/02/2007Michele Faucci Giannelli19 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

07/02/2007Michele Faucci Giannelli20 Backup slides

07/02/2007Michele Faucci Giannelli21 Preparation: calibration Check calibration for pions and electrons Black Pandora Red Wolf LDC01Sc Pions Electrons GeV