ZHH channel: software and detector performances for ILC

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

2. 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 • Particle Flow Algorithm performances • Detector comparison • First look at background • Conclusions Michele Faucci Giannelli

3. 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 Michele Faucci Giannelli

4. 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) Michele Faucci Giannelli

5. Marlin Processors Tracking Processors: • FullLDC: • LEPTrackingProcessor • SiliconTracking • FullLDCTrackin • TrackCheater Marlin 0.9.7 + MarlinReco 0.3 • Processors used: • VTXDigi • FTDDigi • TPCDigi • Tracking Processors • PFA Processors • PairSelector • SatoruJetFinder • BosonSelector • MyROOTProcessor PFA Processors: • Wolf: • TrackWiseClustering • Wolf • ClusterMerge • PandoraPFA: • TrackBasedPFA: Michele Faucci Giannelli

6. 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 Michele Faucci Giannelli

7. Invisible particles PANDORA WOLF Black: normal reconstruction Red: 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 Michele Faucci Giannelli

8. Generators Tree generators: • Pandora Pythia • Pandora Phytia with K, S, • X, p NOT decayed • Whizard No visible difference noticed Michele Faucci Giannelli

9. Two Tracking algorithms: FullLDC Tracking TrackCheater Tracking No visible difference noticed Tracking is good enough Michele Faucci Giannelli

10. PFA Comparison Z→ee Three PFA available: • PandoraPFA • Wolf • TrackbasedPFA Z→mm Problem in TrackbasedPFA with particle identification Cut on Z mass in the Higgs Plot to select good events Michele Faucci Giannelli

11. Higgs Mass Z→mm 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 Z→ee 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!! Michele Faucci Giannelli

12. Higgs discrimination: D plot • D is defined as Z→mm For muons PandoraPFA is the best algorithm Z→ee For electrons Pandora and TrackbasedPFA are comparable Michele Faucci Giannelli

13. Higgs discrimination: D2 plot • D2 is defined as Z→mm Z→ee Michele Faucci Giannelli

14. Detector comparison Z→mm PandoraPFA LDC00SC LDC01Sc Z→ee No differences in the muon case LDC01Sc is better than LDC00Sc for electron, less material then less bremsstrahlung? Michele Faucci Giannelli

15. First look at Background(I) LDC00Sc TrackbasedPFA Z→ee ZHH ZZHZZZ PandoraPFA Pandora is better not only for a more efficient signal reconstruction but for a smaller contamination too Michele Faucci Giannelli

16. First look at Background (II) LDC00Sc PandoraPFA Z→mm ZHH ZZHZZZ Z→ee Good discrimination for muons, a factor 2 better than electrons. ParticleID has a crucial role, more effort are needed! Michele Faucci Giannelli

17. First look at Background (III) LDC00Sc PandoraPFA ZHH ZZHZZZ Same as previous slide, linear scale Michele Faucci Giannelli

18. 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 Michele Faucci Giannelli

19. 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 Michele Faucci Giannelli

20. Backup slides Michele Faucci Giannelli

21. Preparation: calibration • Check calibration for pions and electrons Black Pandora Red Wolf Pions Electrons GeV LDC01Sc GeV Michele Faucci Giannelli