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Electrons and Photons at CMS and Tests with DØ Data

Electrons and Photons at CMS and Tests with DØ Data. Yuri Gershtein. Outline. The problem precision calorimetry with dead material in magnetic field CMS and DØ detectors / algorithms “CMS-like” algorithm performance in DØ data Z, J/ ,  What is different between CMS and DØ new challenges

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Electrons and Photons at CMS and Tests with DØ Data

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  1. Electrons and Photons at CMS and Tests with DØ Data Yuri Gershtein

  2. Outline • The problem • precision calorimetry with dead material in magnetic field • CMS and DØ detectors / algorithms • “CMS-like” algorithm performance in DØ data • Z, J/,  • What is different between CMS and DØ • new challenges • Outlook Yuri Gershtein - Tev 4 LHC Brookhaven

  3. Electrons and Photons at CMS CMS CMS • Lead Tungstate crystals • Excellent stand-alone resolution • Biggest challenge is the amount of material in front of the ECAL Yuri Gershtein - Tev 4 LHC Brookhaven

  4. Calorimeter: Dense and Finely Segmented 61200 barrel crystals 14648 endcap crystals No longitudinal segmentation Transverse segmentation ~ 0.02 x 0.02 Four longitudinal layers Transverse segmentation ~ 0.05 x 0.05 in shower max ~ 0.10 x 0.10 other layers Yuri Gershtein - Tev 4 LHC Brookhaven

  5. Tracking: Few Precise Measurements Radius ~ 110cm, Length ~ 540cm h~1.7 6 layers TOB h~2.4 4 layers TIB 3 disks TID 9 disks TEC Radius ~ 55 cm, length ~ 260cm 16 layers of Scintillating Fibers (8 axial + 8 stereo) 4 to 8 silicon layers (mostly double-sided) Yuri Gershtein - Tev 4 LHC Brookhaven

  6. CMS: find bumps in calorimeter cluster the bumps in barrel the window size  ~ 0.80.06 DØ “Nearest Neighbor” algorithm (CellNN) find deposits consistent with single particle in each layer Parameters are tuned to avoid EM shower “splitting” Cell energies are shared between clusters according to EM shower size Algorithms Yuri Gershtein - Tev 4 LHC Brookhaven

  7. DØ: Zee with CellNN Mee (GeV) Mee (GeV) • Two highest Et CellNN clusters + two tracks Subset of events which has at least one CellNN cluster near the electron candidate (R < 0.2) Yuri Gershtein - Tev 4 LHC Brookhaven

  8. DØ: Zee with CellNN After correction  Mee (GeV) Mee (GeV)  Before correction for extra clusters • internal + external brems • no “-spray” pattern • bend angle is small Yuri Gershtein - Tev 4 LHC Brookhaven

  9. DØ: J/ and  • A little less dramatic improvement – lower pT and poorer resolution • CellNN threshold is 1.5 GeV – needs to be lowered all before / after Mee (GeV) Mee (GeV) Yuri Gershtein - Tev 4 LHC Brookhaven

  10. When Quantity Transforms to Quality • Many experiments dealt with recovery of energy lost to Bremsstrahlung and dead material • New combination: • huge amount of material in 4T field • excellent intrinsic calorimeter resolution • Effects that were “small” in other experiments are not small any more CMS Tracker material – up to 1.5 X0 DØ Preshower detector – 2.0 X0 CMS curler pT ~ 0.8 GeV DØ curler pT ~ 0.2 GeV Yuri Gershtein - Tev 4 LHC Brookhaven

  11. How Much of Electron Energy Reaches Calorimeter? clusterable too far from the main cluster does not reach ECAL • Run GEANT simulation of CMS • Keep track of all Brems and conversions • Propagate all particles to calorimeter face • bremsstrahlung photons convert and electrons from conversion curl up • So far look in barrel only (Occupancy in endcap is much larger problem) Yuri Gershtein - Tev 4 LHC Brookhaven

  12. CMS Barrel at calorimer face electrons with ET 80 GeV flat in rapidity and azimuth in 0.8x0.06 window How to estimate resolution: determine the window that has 95% of events, calculate RMS in this window ET ET If one knows amount of tracker material one can correct for average lost energy pseudorapidity Yuri Gershtein - Tev 4 LHC Brookhaven

  13. “Small” Effect Resolution before  dependent correction Resolution after  dependent corrections Resolution before  dependent correction Resolution after  dependent corrections Intrinsic resolution of the calorimeter Resolution before  dependent correction  / ET ET 20 40 Yuri Gershtein - Tev 4 LHC Brookhaven

  14. Photons v.s. Electrons photons mean = 39.86 electrons mean = 39.44 95% 95% • Unlike electrons, photons penetrate through material completely intact until the first conversion • Even with perfect calorimeter ~ 1% average difference between electron and photon energy scales @ 40 GeV • 1.5% difference if use only unconverted photons • TDR figure for unconverted photon energy resolution is 0.9% at 35 GeV • If calibration is done with electrons from W and Z -> need to know material in order to derive photon energy scale Yuri Gershtein - Tev 4 LHC Brookhaven

  15. Lessons from Tevatron DATA1000k MC 60k • Material is hard to get right • especially it’s spatial distribution • CDF was not able to use electron track momentum for W mass measurement in Run I • DØ Run II material was initially underestimated by almost a factor of 2 • Engineering drawings do not correspond to “as built” detector Note: the distribution of the material in azimuth is very non-uniform DØ can use -symmetry for calorimeter inter-calibration because calorimeter resolution is worse than in CMS and there is not as much material Yuri Gershtein - Tev 4 LHC Brookhaven

  16. Measurement of Material • Use well-measured resonances, like J/, to tune MIP momentum measurement in tracker • gives “average” material • Photon conversions give full 3-D material distribution that can be fed back to simulation • Challenge is to determine reconstruction efficiency • Some handles from KS – known lifetime • Some handles from symmetric / asymmetric conversions • Very delicate measurement! • The systematic and the tools are quite similar for CMS and DØ (same tracker philosophy - few precise measurements on a track) • Studies in DØ are still ongoing, >3 years into the run… Yuri Gershtein - Tev 4 LHC Brookhaven

  17. Are “Lost” Brems Unrecoverable? • Consider a simplified situation: only one brem per electron occurring at fixed radius • Even if the brem is lost energy and position measurement in ECAL and initial direction measurement from pixel detectors can be used to calculate the energy of the brem and “recover” it • Even the crudest combination already shows correlation:  - (MC) ET Yuri Gershtein - Tev 4 LHC Brookhaven

  18. Full Simulation • Same correlation is clearly seen in the full simulation ( is corrected by bend angle expected from calorimeter energy measurement) (ECAL) - (pixel) Super-cluster ET Yuri Gershtein - Tev 4 LHC Brookhaven

  19. Interplay of Tracker and Calorimeter • an algorithm could be devised that would make a global fit to an electron • allow for track pT changes • identify brems • takes full advantage of the calorimeter – track correlations Yuri Gershtein - Tev 4 LHC Brookhaven

  20. Summary • The DØ data qualitatively confirms that CMS-like Bremsstrahlung recovery works • The problem of Bremsstrahlung recovery at CMS however is not just about finding all clusters in the calorimeter, it’s about correcting for the energy that does not reach the calorimeter at all • Photon and electron calibrations are therefore substantially different • One of the biggest challenges is making a precise measurement of the material before the calorimeter • a tricky measurement • especially hard with a tracker with very few (~10-15) layers • DØ methods/tools for that might be directly applicable to CMS Yuri Gershtein - Tev 4 LHC Brookhaven

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