CMS Tracker Performance Francesco Palmonari (INFN Pisa) on behalf of the CMS Collaboration 8th International "Hiroshima" Symposium on the Development and Application of Semiconductor Tracking Detectors 1 6 december 2011 francesco.palmonari@cern.ch
Outline The CMS silicon tracker Tracker Operations in 2011 Strips and Pixels status Tracker Performances Conclusions Please note: Laser Alignment → A.Perieanu Radiations damages effects → C.Barth 2 6 december 2011 francesco.palmonari@cern.ch
The CMS detector at the LHC 5.7 fb-1 delivered and 5.2 fb-1 recorded by CMS during pp collisions in 2011 LHC Point5: 100 m underground in the comune de Cessy (pays de Gex - FR) ← CERN site Almost 90 μb-1 delivered to CMS during ions collisions as of 28.11.2011 3.8 Tesla magnetic field 3 6 december 2011 francesco.palmonari@cern.ch
The CMS silicon tracker Silicon Strips Pixels 9.6 M channels 66 M channels CMS Tracker 198 m 2 silicon area + 1.1 m 2 silicon area = σ(pt)/pt ~ 1-2% (pt~100 GeV) 10 layers (TIB TOB) 3 layers IP resolution: ~10-20μm 12 disk (TID TEC) 2 disks (pt = 100-10 GeV) ~ 4 stereo hits pitches: 80-180 μm thickness: 320-500 μm NB: 2 sensors-modules are only in TOB and TEC TOB Bpix r = 4,7,11 cm Fpix TIB TID TEC z = 35,47 cm 4 6 december 2011 francesco.palmonari@cern.ch
Tracker operations in 2011 Standard operations: ● Periodic calibration: pedestals, noise, optical receiver offsets ● Periodic bias scan to monitor the radiation damage: - leakage current increasing everywhere as expected pixels: strips: measured V dep decrease as expected - iLeak measured on board of modules (dcu) and from caen power system - no V dep change for >5fb-1 (expecting < - 10 V) CMS Preliminary 5 6 december 2011 francesco.palmonari@cern.ch
Tracker operations in 2011 Uptime: > 98% with stable conditions ● Strips cooling: stable coolant 4 Celsius; leaks controlled to <0.7 kg/day ● Pixels cooling: stable coolant 7 Celsius ● Power/Detector Control System (DCS): stable had <1% PSU replaced ● Electronics: stable. ● Data Quality Monitoring (DQM): stable. prompt feedback provided to Operations Coordinators Full reconstruction chain monitored online and offline with: raw data – Digis – on track/off track clusters - track reconstruction histograms CMS data taking efficiency: ~91% in pp ~96% in ions** ** = as of the 04.12.2011 Luminosity lost by category (pp) ~9% in 1935 runs 28% because of tracker DAQ: 26% (18% strips and 8% pixels) POWER: 2% (1% strips; 1% pixels) Please note: (strips+pixel) constitute the 70.6% of the CMS DAQ (480/680 FEDs) 6 6 december 2011 francesco.palmonari@cern.ch
Strips detector status In this map: permanent defects not used not used good good total alive channels fraction: 97.79% TIB: 94.3% TID+-: 98.1% TOB: 98.2% TEC+:98.8% TEC-:99.1% 5 loops with passive cooling only. NB: possibility to recover 0.5% of the channels during the shutdown LS1 7 6 december 2011 francesco.palmonari@cern.ch
Pixel detector status Active channels fraction: 96.9% (Barrel 98.4 % ; Disks 92.8 %) percentage of dead channels: 3.1% location of the dead pixel in the occupancy maps: NB: ~3% of Fpix missing due to the loss of an Analog Opto Hybrid (AOH) in 2010 8 6 december 2011 francesco.palmonari@cern.ch
Cluster reconstruction (strips) Two possible signal readout modes: - deconvolution: standard mode for physics weighted sum of 3 signal samples - peak: full signal sample; in this mode the noise is ~0.3 lower but time resolution is worst S/N distributions from on-track clusters after correcting for the path length. Distributions below use the signal taken in deconvolution in the inner (thin) and outer (thick) barrel sensors. - S/N = (cluster signal) / (noise of strips) - Signal maximized after fine delay adjustment (next slide) 320 μ m sensors 500 μ m sensors 9 6 december 2011 francesco.palmonari@cern.ch
Timing optimization Random Time Delay Scan: measure the signal position w.r.t the nominal sampling point deviations (from 0) are within 1 ns signal profile has the expected 12 ns width Pixels: delay scanned maximizing the on track cluster size; choose phase delay in order to have enough room within the efficiency plateau 10 6 december 2011 francesco.palmonari@cern.ch
Hit resolution Hit resolution depends on sensor thickness and strip pitch: the minimum value is reached for an angle corresponding to optimal charge sharing Obtained hit resolutions: Strips: 15 μ m to 45 μ m pitch degrees Layers μ m 0-10 TIB 12 80 16.0 ± 3.5 TIB 34 120 27.9 ± 2.9 TOB 1234 183 41.3 ± 3.8 TOB 56 122 24.5 ± 2.7 Pixels: 9 μ m to 35 μ m with 2 independent method: - Overlaps (shown in the plot) - Hit triplets 11 6 december 2011 francesco.palmonari@cern.ch
Tracks reconstruction Using Kalman filter technique for high track density environment: Seeding → Pattern recognition → Track fitting • Seeding: pixel hit triplets or pixel/strip hit pairs with constraint from the beam spot • Iterative tracking (7 iterations) • at each iteration remove track-assigned hits and relax seed cuts Track parameters agreement with MC samples (Pythia 8 and GEANT4) Event selection: good collision events defined by trigger and vertex selections criteria Track selection: σ (p t )/p t < 5% and d z <10 σ 12 6 december 2011 francesco.palmonari@cern.ch
Alignment - Increased local precision w.r.t. 2010 - Control of the weak modes with mass constrain Z → μ+ μ− - accounting for sensor bows and kinks (from 56k parameters to 200k) - correcting for time dependent large (< 30 μ m) pixel volumes movements as part of the PV validation 13 6 december 2011 francesco.palmonari@cern.ch
PV resolution and efficiency PV resolution: depends on the number PV efficiency depends on the of tracks used and their p t num. of tracks of the PV cluster D ata driven “split” method Fakes tracks excluded (by p t cut) provide PV-resolution[number of tracks] split method used within cluster 14 6 december 2011 francesco.palmonari@cern.ch
Tracking performance (pp collisions) Data driven technique to measure the tracking efficiency ( μ shown as example): embed simulated track in Min. Bias Data → test if track is still reconstructed Event average pile-up (PU) increased going from ~5 to ~10 in sept.2011 But tracking and vertexing showed no performance degradation 15 6 december 2011 francesco.palmonari@cern.ch
Particles identification Modules Analog readout allow particles identification using the energy loss information (at least 10 hits/deposits along tracks for dE/dx): 1) a synchronization pulse is used as measure for the electronic gain 2) all signals are normalized to a default value of that pulse 3) the MIP are used to equalize the sensors response by applying particle gain calibration factors 4) these factors are applied so that all sensors and readout chains have equal behavior and the measured charge can be used for particles ID exploiting dE/dx dE/dx validated with Λº → pπ decays Where lower momentum particle is always the π 16 6 december 2011 francesco.palmonari@cern.ch
Conclusions The CMS tracker is part of a marvelous detector: - The CMS tracker is a stable and reliable system providing expected performance for S/N, hit resolution and track reconstruction. It is also used for particle identification. - Such performance are mandatory to produce outstanding physics analysis results The CMS tracker ready to sustain the 2012 data taking where a further increase of the luminosity to integrate is foreseen 17 6 december 2011 francesco.palmonari@cern.ch
Thanks ! References 1. CMS Luminosity Collision Data, https://twiki.cern.ch/twiki/bin/view/CMSPublic/LumiPublicResults. 2. The CMS Collaboration, The CMS Experiment at the CERN LHC, JINST 3S08004 (2008). 3. CMS Tracker Detector Performance Results, https://twiki.cern.ch/twiki/bin/view/CMSPublic/DPGResultsTRK. 4. The CMS Collaboration, Tracking and Primary Vertex Results in First 7 TeV Collisions, CMS Physics Analysis Summary, CMS PAS TRK-10-005 (2010). Special thanks to: Laura, Erik, Andrea, Adrian, Derek, Matthew, Gordon, Petra, Victor, Daniel, Karl, Frank 18 6 december 2011 francesco.palmonari@cern.ch
Backup... detector ;) 19 6 december 2011 francesco.palmonari@cern.ch
backup !! CMS 2011 RECORDS !! 20 6 december 2011 francesco.palmonari@cern.ch
backup S/N ratio last year: 21 6 december 2011 francesco.palmonari@cern.ch
backup Hit resolution: the overlap method Obtained via the comparison between: measured and predicted hit position from track fitting in the overlap regions (within the same tracker sub structure in order to minimize effects of track extrapolation and amount of material transversed) Track reconstruction: seeding → pattern recognition → track fitting explained 22 6 december 2011 francesco.palmonari@cern.ch
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