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Physics Implications of the AFE II Upgrade

Physics Implications of the AFE II Upgrade. Mike Hildreth with Juan Estrada, Charly Garcia, Bruce Hoeneisen in consultation with the hardware experts. Questions. To narrow the focus we are trying to answer two questions: What is the physics cost of NOT doing the AFE upgrade?

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Physics Implications of the AFE II Upgrade

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  1. Physics Implications of the AFE II Upgrade Mike Hildreth with Juan Estrada, Charly Garcia, Bruce Hoeneisen in consultation with the hardware experts Mike Hildreth – AFE II Director’s Review

  2. Questions To narrow the focus we are trying to answer two questions: • What is the physics cost ofNOTdoing the AFE upgrade? • Model all effects of the current system plus all those that degrade the tracker performance at high luminosity • Use b-tagging performance in Zbb events as a benchmark • Studies of luminosity cost for top mass, Higgs searches • What are the benefits of adding timing information to CFT hits? • Realistic model of timing with known electronics behavior • provide performance basis for previous tracking studies Mike Hildreth – AFE II Director’s Review

  3. Overview • Summary of CFT simulation details • “basis of estimate” for all results • signal generation • degradation at high luminosity • min-bias model • Results for Question 1: Cost of not doing the upgrade • Simulation of timing information from the Trip-T • Results for Question 2: Benefits of the upgrade Mike Hildreth – AFE II Director’s Review

  4. Default CFT Monte Carlo • Energy Deposition of Geant particles, mapping to fibers, photon generation: • Photons ordered by arrival time at VLPC, converted to photo-electrons • Total charge calculated, including sampling distribution single Geant volume All of this is incorporated in the “Digitization” portion of the CFT MC Mike Hildreth – AFE II Director’s Review

  5. Modifications to the CFT Simulation • The results presented here are based on a new version of the CFT digitization code that includes: • realistic light yields • realistic gain spectra • realistic thresholds • small amount of pedestal noise to simulate threshold spread • (readout thresholds have one setting for 64 channels) This simulation provides the “Current CFT” detector model (One thing missing: tick-by-tick pedestal shifts) Mike Hildreth – AFE II Director’s Review

  6. Modifications for High-Lumi CFT • For purposes of comparison, we have created a “CFT 2007” simulation to model the “un-upgraded” AFE system at high luminosities. This includes: • degradation of CFT light yield by 18% from radiation damage • VLPC gain is lowered by 18% due to high singles rates • (total of 40% signal loss) • higher readout threshold (1.5  2.5 p.e.) • this would be implemented to fight the occupancy caused by the pedestal shifts • SVX pedestal shifts as a function of occupancy • at 32% occupancy (linear with occupancy) • SIFT1: -1pe, SIFT2: -0.5pe, SIFT3: +1pe, SIFT4:+3pe • Saturation of SVX response according to bench tests Mike Hildreth – AFE II Director’s Review

  7. Minbias Simulation • Total Pythia cross section for latest tune is 59mb • includes single- and double-diffractive events • lower-occupancy contribution • comparison of minbias data taken at low luminosity with Pythia events • “proper” extraction of occupancy, subtracting zero-bias and correcting for multiple interactions • occupancy for only those (single) MC events that pass minbias trigger • Here, a mean of 12 min-bias interactions/crossing corresponds to approximately =3x1032/cm2/s Mike Hildreth – AFE II Director’s Review

  8. Simulation Results: Saturation Effect • Example from ttbar events • top events interspersed with “single neutrino” events to simulate saturation effects vs. beam crossing number • SVX response begins to saturate (slowly) after 9 p.e., fully saturated above 100pe • Drastic reduction of track multiplicity, number of CFT hits; lumi-dependent • effect much worse at higher luminosities Number of Tracks per beam crossing ttmnb+jjb Number of CFT Hits per beam crossing Mike Hildreth – AFE II Director’s Review

  9. default MC Simulation Results: Single Hit Efficiency • Degraded events have more clusters (~10% at highest luminosities), produce up to 40% more tracks per event • due to lower light yield, higher thresholds to mitigate the effects of SVX pedestal shifts • (show this plot?) Degradation of single-muon finding efficiency in topWb decays normalized to current CFT model ttmnb+jjb Mike Hildreth – AFE II Director’s Review

  10. Simulation Results: b-tagging • numbers from Gordon on ttbar, ZH->nunu bbbar Mike Hildreth – AFE II Director’s Review

  11. Luminosity Cost of Status Quo • Plots showing extra luminosity needed relative to upgrade case for top mass (reco efficiency-based, lepton + btag) and ZH (b-tagging) Mike Hildreth – AFE II Director’s Review

  12. Trip-T Timing Studies • “Real” CFT MC used as a basis for detailed studies of photo-electron charge deposition and timing: • “standard” CFT simulation has always included the generation and propagation of individual scintillation photons • directions, capture in fiber, reflection off of polished end, etc. • waveguide lengths/losses, quantum efficiency, etc., also simulated • statistical sampling of charge generation • Time over discriminator threshold is encoded with ADC (or p.e.) information so it is available to Reco • individual photons sorted by their arrival time • all photons from all MC particles hitting a fiber are generated before any charge deposition simulation takes place • proper simulation of charge deposition with “real” thresholds • “Time” is set when total charge crosses the channel threshold Mike Hildreth – AFE II Director’s Review

  13. Trip-T Timing Studies II • Motivations for this study: • Allows “confirmation” of expected time resolution • previous studies based on toy MC without real detector geometry, photon propagation, etc. • Study timing performance, time “purity” of hits in high-occupancy events • evaluate prospects for time-based track reconstruction without rewriting the entire tracking code first • validate earlier studies of tracking timing improvement • Event samples:15 high-pT muons per event • zero minbias baseline • 3, 6, 9, 12 minbias overlay • see effects of increasing occupancy on timing info Mike Hildreth – AFE II Director’s Review

  14. Timing Data in CFT Monte Carlo • sigma of time resolution for single muon tracks is 1.8- 2.2 ns • Shown here for |h|<0.2 • expected evolution of resolution with h of track • s(z)=2 ns * 18cm/ns = 36 cm Mike Hildreth – AFE II Director’s Review

  15. Timing Data in CFT Monte Carlo • Expected correlation (“time-walk”) of low-ADC signals clearly seen in simulation • can be corrected on average for better timing resolution for all hits • not done yet for these studies Mike Hildreth – AFE II Director’s Review

  16. Z position Reconstruction • Track Z position compared with time of hits (no minbias overlayed here) • Only hits with large charge deposition (>10 p.e.) are used to avoid “time-walk” effects • works as expected • “wiggle” due to timing effects from reflected photons (poorer resolution beyond z=0) Mike Hildreth – AFE II Director’s Review

  17. Timing Results at Higher Occupancy • Clearly, the width of clusters increases as occupancy goes up • same events, same muon tracks, higher occupancy • must be from background hits • What happens to time resolution? Mike Hildreth – AFE II Director’s Review

  18. Time Resolution vs. Occupancy • For events with 9mb overlaid, timing (z) resolution vs. CFT layer. • not ruined by occupancy • outer layers fare better than inner layers, as expected rms = 28.2cm rms = 26.2cm rms = 28.0cm rms = 24.9cm Mike Hildreth – AFE II Director’s Review

  19. More Timing Results • Timing cut: efficiency vs. rejection for various layers, multi-muon events, 9mb events overlaid (12mb looks similar, slightly worse) • here, “fake” hits are those on found tracks which are caused by another MC particle besides one of the muons Layer 1 Layer 4 Layer 8 (.9,.74) (.9,.32) (.9,.42) Mike Hildreth – AFE II Director’s Review

  20. Good vs. “Spoiled” Hits • time residuals for good hits (top), bad hits (from other MC particles, bottom) • many “bad” hits are close in apparent z position to correct hits • some tails • (hatched area is 98% efficiency for good hits) • (muon events, 12mb) Mike Hildreth – AFE II Director’s Review

  21. Good vs. “Spoiled” Hits • calculated z position vs. time for “good” hits (matched to MC track) and “spoiled” hits (contaminated by other MC particles) • Spoiled hits are often close in true z position, or at least correlated • less true on inner layers • (muon events, 12mb) “good” hits “spoiled” hits Mike Hildreth – AFE II Director’s Review

  22. Timing in Zbb events • Zbb, 12 minbias overlaid • time resolution of hits on found tracks • note tails on inner layers • outer layers still relatively clean • core resolutions similar in all cases, slightly worse than single muons Layer 1 Layer 3 Layer 6 Layer 8 Mike Hildreth – AFE II Director’s Review

  23. Comments on Tracking Improvements • Comments on Guennadi’s study (DØ Note 4497): • Done with 25cm resolution in z position of hits (cut at 3s) • c.f. ~40cm • Done with 15 minbias events • Done by assigning the z position of the first photon in the fiber to that hit (no time-over-threshold simulation) • Occupancy effects included • Used for forming 2-D (axial+stereo) hits only • no attempt to “break” clusters that have fibers with different times associated with them • Guennadi saw a 40% reduction in cpu time, with no eff. loss • Conclusions probably wouldn’t be so different with this MC Mike Hildreth – AFE II Director’s Review

  24. Comments on Tracking Improvements • AFEII has several additional benefits for tracking algorithms: • improvements in single-hit resolution by forming CFT clusters only from fibers that are contiguous in time • Better ADC information: • removes saturation effects on ADC • removes pedestal shifts • removes split pedestals • removes tick-to-tick variation  recoups much of lost tracking, b-tagging efficiency • May allow cluster-splitting, or better single hit resolution using charge sharing • quantification requires a lot more work Mike Hildreth – AFE II Director’s Review

  25. Tracking with Discriminators Run 192539 Lumi ~8x1031 Axial disrc. Default Mike Hildreth – AFE II Director’s Review

  26. Tracking with Discriminators • Real data used • Axial discriminators used instead of normal ADC information • (not a true test – optimistic in terms of timing) • Tested on high-luminosity run (Run 196234, ~8E31) • Tracking efficiencies pretty much identical • Extra CFT-only tracks found with Discriminator tracking • probably fakes... • Relative timing: • default maxopt reco (p17.02): 26.98 sec, 142.25 trks/event • discriminators used: 30.01 sec, 174.86 trks/event • 10% slower, 23% more tracks Mike Hildreth – AFE II Director’s Review

  27. Tracking with Discriminators • Comments: • discriminators hard to calibrate • requires dedicated data runs • digital-only tracking will have no diagnostics behind it • no handle for noise suppression (like the 20-adc cut we use) • stereo discriminators do fire, even when the threshold is set to 255 – pedestals will shift, even on stereo boards • Stereo boards never commissioned for discriminator operation • “several bodies buried” in Stereo crates • stereo board = axial board that failed discriminator tests • commissioning time unknown • no clear strategy for repair, or use of spares Mike Hildreth – AFE II Director’s Review

  28. Conclusions • Current SVX-SIFT AFE will seriously degrade the tracking performance at high occupancies • Saturation may be the dominant effect • already evident in data • may be responsible (already) for poor tracking in forward regions • under study • Trip-t timing will be useful for pattern recognition • will eventually be limited by multi-hit fibers • outer layers can still benefit even to the highest luminosities • one more handle to combat high occupancies Mike Hildreth – AFE II Director’s Review

  29. Backup Slides Mike Hildreth – AFE II Director’s Review

  30. Necessary Software Modifications • Unpacking: • unpack_ft_fe • AFE-board classes • cft_unpdata • raw  fiber space • sftdigi_evt • SFTDigiChunk • Monte Carlo • sftdigi • CFTReadoutSim • packer for MCRaw • sftdigi_evt • SFTDigiMCChunk • Reco: • cft_evt • CftClusterChunk • d0om packing • CftClusterMCChunk • cft_reco • Clustering algorithms • (Tracking Algorithms) • Databases: • t0 per channel or sector • additional constants Mike Hildreth – AFE II Director’s Review

  31. Timing Performance at High Occupancy • Change in “time c2” at high occupancy (9 minbias events overlaid) • S(ztrack-ztime)2/sz2 • Shift, but most of the peak still has decent c2 • “global” timing resolution still ok at high occupancy Mike Hildreth – AFE II Director’s Review

  32. Timing Data in CFT Monte Carlo • sigma of time resolution for single muon tracks is about 2.4 ns • Shown here for |h|<0.2 • expected evolution of resolution with h of track • s(z)=2.4 ns * 18cm/ns = 43cm Mike Hildreth – AFE II Director’s Review

  33. Some plots (current tune) Light yield vs. h: Data MC Oana Boeriu Axial Axial Stereo Stereo Mike Hildreth – AFE II Director’s Review

  34. More plots • Light yield comparisons for data and MC (with zero-bias events overlayed) • “most probable” values (fit peaks) are similar in both • Detailed understanding of MC/Data differences in light yield spectra are under study • Possible role of SVX Saturation Mike Hildreth – AFE II Director’s Review

  35. Z  bb Event Simulation • Several samples generated so that the progressive addition of defects could establish a clear trend • Same 1000 Zbb events used for each sample • Here, 12mb corresponds roughly to 3x1032 instantaneous Lumi • Samples: • “default” MC, 0 minbias overlay = “perfect” • “default” MC, 12 minbias overlay = “messy” • “realistic” 2004 CFT, 12 minbias = “current + messy” • “bad sift” 2007 CFT, 12 minbias = “degraded + messy” • “saturated” 2007 CFT, 12 minbias = “worst performance” Mike Hildreth – AFE II Director’s Review

  36. b-tagging results • SVT Tagger per-jet forward-tag efficiencies for all B jets: • no discernible difference in backwards tags • up to 40% loss in relative efficiency compared with 2004 MC • AFEII recoups about 75% of this efficiency loss Mike Hildreth – AFE II Director’s Review

  37. b-tagging results • JLIP Tagger per-jet forward-tag efficiencies for all B jets: • no discernible difference in backwards tags • up to 15% loss in relative efficiency compared with 2004 MC • AFEII recoups about 75% of this efficiency loss Mike Hildreth – AFE II Director’s Review

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