Commissioning of the Silicon Drift Detector of the ALICE experiment - - PowerPoint PPT Presentation

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Commissioning of the Silicon Drift Detector of the ALICE experiment - - PowerPoint PPT Presentation

Oct 31, 2022 282 likes •689 views

Silicon Drift Detector of ALICE Calibration Conclusions Commissioning of the Silicon Drift Detector of the ALICE experiment at the LHC Emanuele Biolcati for ALICE collaboration Dipartimento di Fisica dellUniversit` a di Torino INFN Torino

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Silicon Drift Detector of ALICE Calibration Conclusions

Commissioning of the Silicon Drift Detector

  • f the ALICE experiment at the LHC

Emanuele Biolcati for ALICE collaboration

Dipartimento di Fisica dell’Universit` a di Torino INFN Torino

XLVII International Winter Meeting on Nuclear Physics Bormio - Jan. 26-30, 2009

1 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

Outlines

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Silicon Drift Detector of ALICE Detector Physics

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Calibration Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

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Conclusions

2 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

ALICE experiment @ LHC

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

Pb-Pb event @ LHC (simulation)

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

The Inner Tracking System

Pixel (SPD) 240 sensitive volumes Drift (SDD) 260 sensitive volumes Strip double-side (SSD) 1698 sensitive volumes Resolution Detector xloc [µm] zloc [µm]

  • ccupancy [%]

SPD 12 70 1.5 - 0.4 SDD 38 28 2.5 - 1.0 SSD 20 830 4.0 - 3.3

5 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

ALICE Silicon Drift Detector

Anodes 256 × 2 Cathodes 291 × 2 Anode pitch 294 µm Cathode pitch 120 µm HV (nominal)

  • 1800 V

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

ALICE Silicon Drift Detector

Anodes 256 × 2 Cathodes 291 × 2 Anode pitch 294 µm Cathode pitch 120 µm HV (nominal)

  • 1800 V

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

The SDD module

front back

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

The SDDs inside the ITS

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

Physical motivations of ITS (I)

Primary vertex reconstruction → Secondary vertex reconstruction Track impact parameter

9 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Detector Physics

Physical motivations of ITS (II)

Complement TPC tracking Standalone tracking

10 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Outlines

1

Silicon Drift Detector of ALICE Detector Physics

2

Calibration Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

3

Conclusions

11 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Baseline and noise

4 readout chips per SDD semi-module ⇒ different response function for each chip ⇓ equalization of the baseline calculation of noise per anode (133k) extimation of the common mode noise tag of good/bad anodes

12 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Baseline and noise distribution

Calibration run results baseline equalized to 20 ADC raw noise ≃ 2.3 ADC signal peak by a MIP (close to the anodes) ≃ 120 ADC w/o common mode noise ≃ 1.9 ADC good anodes ≃ 99.5%

13 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Baseline and noise stability (during cosmic runs of 2008)

14 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Gain measurement

test pulse = signal self-generated by the amplifier ⇓ measurement of the gain of the amplification chain

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Gain stability (during cosmic runs of 2008)

gain ≃ 1.28 ADC/DAC variation due to a change of the ADC sampling rate (from 40 MHz to 20 MHz)

16 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

The importance of the drift speed

  • vdrift = µe E

µe ∝ T(K)−2.4 ALICE SDD requirement: σx ∼ 40µm ⇓ drift speed very sensitive to temperature variations ⇓ need to measure (frequently) the drift speed value in many positions of the sensitive region of the detector

17 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Drift speed calculation

3 rows of 33 MOS injectors per semi-module ⇓ drift speed calculated in 33 positions (from linear fit of 3 points) ⇓ distribution vs anode position reflects temperature effects

18 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Drift speed vs module

19 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Drift speed vs time

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Reconstruction of a cosmic ray in the ITS

before calibration after calibration Cosmic charge cluster →

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Charge distribution in SDD

Cluster distribution from cosmic tracks (fitted with a convolution of Landau+Gaussian)

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Data vs simulation

most probable value for energy deposition of a MIP in 300 µm of silicon ⇓ conversion factor from ADC units to keV

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Charge vs drift distance

dependence on the distance between impact point and the collection anodes ⇓ possible reasons: traps in Silicon, signal tails cut by threshold ⇓

  • ffline correction of the measured charge value

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Charge vs drif distance: data and simulation

25 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

Offline correction

26 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions

Outlines

1

Silicon Drift Detector of ALICE Detector Physics

2

Calibration Front-end electronics: noise and gain SDD parameter: drift speed SDD response: charge collection

3

Conclusions

27 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions

Conclusions

Commissioning results 97.6% of SDD modules in acquisition (in 2008) Detector calibration parameters stable and stored automatically after each calibration run in the ALICE calibration database:

noise gain drift speed (temperature)

Charge conversion factor fine tuned and charge dependence on drift lenght corrected SDDs are ready for p − p collisions

28 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Silicon Drift Detector of ALICE Calibration Conclusions

Ready to go

Z-φ raw occupancy from particles generated by LHC beam dump (September 2008)

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That’s all, thanks.

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Backup

Extra slides

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Calibration files in the OCDB

CalibSDD contains:

baselines, noise and gain for each anode flag for bad module, bad chip, bad anode flag for zero suppression and sampling frequency

updated: by the preprocessor after each PEDESTAL+PULSER runs RespSDD contains: time offset, conversion factor ADC → keV updated: after offline analysis

  • f reconstructed points

DriftSpeedSDD contains: drift speed (parametrized) vs anode number updated: by the preprocessor after each INJECTOR run

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Temperature vs module

  • vdrift = µe E

µe ∝ T(K)−2.4 ⇒ T(K) = 293.15 vdrift/E µe(293K) − 1

2.4 33 Emanuele Biolcati Commissioning of the ALICE Silicon Drift Detector

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Noise of common mode

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Charge vs drift lenght

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Time zero: residuals method

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Time zero extraction methods

  • 1. Minimum drift time

how: extraction from time distribution of all the measured clusters why: no need to use calibration quantities, no need to use information from

  • ther layers

why not: large statistics of RecPoints required

  • 2. Track cluster residuals

how: extracted by exploiting the opposite sign of residuals in the two detector sides why: requires less statistics required why not: requires use of drift speed and correction maps, requires track reconstruction in the SPD or SSD

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Time zero: simulation and data

Simulation the results are consistent Data method 1 is not applicable method 2 gives incoherence ⇓ under investigation

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Doping inhomogeneities

Array of 520 AliITSMapSDD objects ⇓ systematic deviations on the drift time coordinate of the reconstructed points

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