Calibration and alignment software

1
Calibration and alignment software

• Marian Ivanov

2
Outlook

• Impact of systematic effects on physical results
• TPC calibration
• TPC alignment

3
Statistical uncertainty

• R-Phi and Phi resolution for perfectly aligned
  and calibrated TPC (at the TPC entrance)
• Given by the cluster position resolution (
  divided by sqrt(Npoints))
• At low momentum influence of the multiple
  scattering

4
Misalignment of detectors

• Linear misalignment can be detected by our
  algorithm
• Statistic of 2000 tracks per sector (IROCOROC)
  ( 72000 tracks) is big enough to be on the level
  below statistical uncertainty
• Tested with stand-alone (fast) simulator
• Following slides precision of the alignment
  parameter determination for two different
  statistic sets

5
Track fitting

• AliRieman used for track fitting
• Less than 1 s for track fitting (20000 tracks)
• Picture
• Pt resolution for non aligned sectors
• Input misalignment
• 2 mm in translation
• 1 mrad rotation

1/ptrec-1/pt
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Results Rotation Z

• Left side 2000 track samples
• Right side 5000 track samples

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Translation X

• Left side 2000 track samples
• Right side 5000 track samples

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Translation Y

• Left side 2000 track samples
• Right side 5000 track samples

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Result (Pt residuals)

• Relative pt resolution (dpt/pt)
• Left side before alignment
• Right side after alignment

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Alignment - ExB

• ExB effect simulated linear dependence
  expected
• Xshift kx(z-250) kx0.005
• Yshift ky(z-250) - ky0.005
• The same in both sectors
• Alignment with tracks (2000 track samples)
• Systematic shifts in translation estimates
  (negligible in comparison with statistical error)
• X 0.02 mm, Y 0.08 mm, Z 0.003 mm
• Systematic shift in rotation estimates
• Rz 0.05 mrad, Ry 0.006 mrad, Rx 0.006 mrad

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Warning example - STAR - TPC GridLeak distortion

• Dependence on field, track charge, location,
  luminosity consistent with ion leakage at gated
  grid gap
• Hopefully not the case of Alice TPC

12
Alice ExB distortion (M.Kowalski)

• Radial distortions at lower and outer TPC radius
  due to the nonuinformity of magnetic field E
  field perfectly aligned with B field at central
  membrane
• Alice - Omega tau 0.354 (E400V/cm, B0.5T)
• Note
• Non linear as function of z
• Phi dependence

13
Alice ExB distortion (M.Kowalski)

• Azimuthal distortions at lower and outer TPC
  radius due to the nonuinformity of magnetic field
• Dy 90cm x 0.0018 0.16 cm (STAR reported
  magnitude of correction on the level 0.1 cm
  nucl-ex/0301015)
• Systematic error - 4 times bigger than
  statististical

14
Alice ExB distortion

• Influence
• Systematic effect to the DCA resolution
• The distortion z and theta dependent
• For the first analysis the cut on the DCA has to
  be adjusted
• The influence on the pt resolution will be
  estimated
• Realistic magnetic field description needed (see
  next slides)
• Track finding efficiency in TPC should be not be
  affected (ExB distortion is a smooth function)
• Influence on the TPC-ITS track matching

15
L3 field components
Tesla calculation (M.Losasso)currently in
Aliroot I 30 kA
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L3 field components
Measured field, I 30 kA (from ntuples of
A.Morsch) No corrections for possible probes
misalignment applied
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Drift velocity

• Requirements (systematic error on the level of
  statistical error)
• Z resolution 0.01 cm
• vdrift precession 0.410-4
• Measurements
• Drift monitor GOOFY 10-4
• Tracks crossing central membrane
• STAR TPC
• (Initial) drift velocities determined / monitored
  with lasers
• Automated updating of drift velocities (and
  initial T0) from laser runs
• Checked / fine-tuned by matching primary vertex Z
  position using east and west half tracks
  separately (Alice algorithm tested by
  C.Cheskov)
• Ideally determined from track-matching to SVT
  (perpendicular drift), but requires all other
  calibs to be done already! (principle has been
  tested)

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Electron attachment

• Electrons can be absorbed in the gas during the
  drift
• The probability to be captured by an O2 molecule
  is 1 per 1 m drift per 1 ppm of O2 (NA49)
• Alice expected oxygen content (ALICE MC) 5 ppm
• Should be achieved (Joachim)
• Influence
• Non systematic effect to the position resolution
• Affects only statistical uncertainty by a factor
  sqrt(absorbtion) and dEdx measurement
• Does not affect multiplicity measurement

19
Gain calibration

• The chip gains vary in range of 5
• Expected cluster position variation on the level
  of 0.05 pad width
• Expected random behavior
• The gain variation due to electrostatics (for
  example anode wire sagita)
• does not affect the cluster position (the
  effect of local variation of gain is negligible
  as compared to cluster size)
• Influence
• Small influence on the pt resolution and
  efficiency
• dEdx affected

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TPC calibration Outlook

• TPC calibration parameters
• TPC calibration classes
• MI approach
• The size of the calibration data in CDB
  (Condition Database) and in memory (during
  reconstruction) dominated by the size of data for
  pad by pad. Everything else negligible.
• ? Store all data which can be used in the
  reconstruction, respectively which can used to
  indicate problems.
• Particularly the data from the sensors (voltages,
  currents, temperature sensors)
• Offline code status

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Calibration classes

• AliTPCCalDet
• Calibration parameters specific to each sector
• One array of 72 floats
• AliTPCCalPad
• Parameters specific to single Pad
• GainFactor, T0, Pad Response Function Width,
  Noise
• Used to pattern local variations of detector
  parameters
• One array of 72 AliTPCCalROC objects
• AliTPCCalROC
• Actual container of single ROC specific data
• One array of Nchannels floats
• Nchannels depends on the type of sector in stack
  (inner, outer)
• Interface
• AliTPCCalROC(Int_t sector)
• SetValue(padrow, pad, value)
• GetValue(padrow, pad)
• Memory consumption
• Npads x sizeof(value)
• 0.5 million channels sizeof(value)

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TPC calibration parameters per pad
Parameter N. of channels Unit Source Update frequency
Gain factor 557568 Relative Offline/HLT Rare
Time 0 557568 Relative ? Offline/HLT Rare
Preamp-shaper width 557568 Relative ? Offline/HLT Rare
Noise 557568 Relative (sigma) ? Rare

• The difference between relative and absolute is
  in the data volume
• 2MBy relative
• 8 MBy absolute
• Current implementation in AliRoot use floats

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TPC conditions per set of sensors
Parameter N. of channels Information Source Update frequency
Temperature probes 4500 sensors on FEC, snesors on space frame? ?? Interface to DCS Array of ID, position, samples (temparature) in time DCS and ? Per run
High voltage ? Array of ID, samples (voltage and current) in time DCS Per run
Drift voltage (VHV) ? Array of ID, samples (voltage and current) in time DCS Per run
Gating voltages ? Array of ID, voltage DCS Per run
Laser parameters Array of ID, position, angles ? Per surveyer measurement

• The format should be defined as soon as possible
• Avoid problems with versioning
• Define queries
• Data volume depends on the sampling frequency
• Can be reduced by fitting
• The data format and functionality Not TPC
  specific
• Common class should be defined
• Request for offline group presented (Hopefully
  someone will implement it)

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TPC calibration parameters per TPC
Parameter N. of channels Information Source Update frequency
Oxygen content 1 Samples in time DCS Per run
Drift velocity monitor (Goofy) 2 Samples in time DCS? Per run
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Altro setup
Parameter Data volume Source Update frequency
Altro frequncy 0
Altro acquisition window 0
Moving average (on/off) 0
Zerro suppresion (on/off) 0
Tail cancelation (on/off) 0
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TPC calibration parameters per TPC
Parameter Data volume Source Update frequency
Drift velocity map (parameterization) ? Offfline Rare
Space charge map ? Offline Rare
ExB correction map ? Offline Per change of magnetic field

• The above result in the distortion map
• The data volume depends on the grid size

27
TPC parameters for reconstruction
Parameter Data volume Source Update frequency
Signal shape parameterization (diffusion parameter) 0 Offfline Rare
Local error parameterization () 0 Offline Rare
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Shuttle Schema

• AliShuttle The Shuttle program manager.
  Organizes conditions data retrieval,
  preprocessing and storing it to CDB.
• AliShuttleConfig Interface to the configuration
  stored into LDAP server
• AliDCSClient Provides DCS API. Communicates
  with DCS AMANDA server over TCP/IP
• AliShuttleTrigger Interface to
• DAQ LogBook and client to DAQ End of Run
  notification service

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Offline calibration - Status

• Calibration classes for pad parameters
  implemented
• Default parameters stored in the database
• Pad gain variation (- 5)
• Used in simulation and reconstruction
• Noise, T0, and Preamp shaper width - will be
  implemented soon in the simulation
• Typical variation of parameters needed as input

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Alignment - Outlook

• Toy model results presented in previous slides
• Short overview of reconstruction framework
  (Cvetan Cheskov)
• Current development
• Implement alignment algorithms inside of AliRoot
  alignment framework

31
Alignment framework

• Space-points extraction and processing
  (filtering)
• Track fitting
• Track extrapolation points
• Residuals minimization

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Framework Overview 1/2
Phase III
Phase IV
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Space-points retrieval (Phase I)

• During the reconstruction, in between backward
  propagation and refitting
• Loop over ESD tracks and sub-detectors
  (ITS,TPC,TRD,TOF,RICH)
• Get cluster indexes
• Call trackers to get the space points
• Store the points inside the ESD track
• The storage of space-points is controlled by
  AliReconstructionSetWriteAlignmentData()
• Unified AliESDtrack method of getting clusters
  and their indexes
• GetNcls(Int_t iDet) GetClusters(Int_t iDet,
  UInt_t)
• Abstract method of AliTracker
• GetTrackPoint(Int_t index, AliTrackPoint p)
• Method implemented for ITS,TPC,TRD,TOF

34
Space points filtering (Phase II)

• Filtering
• Take the ESD trees in a TChain
• Select on ESD track parameters
• Store selected space point arrays into tree (in
  local file) for further analysis
• So far a simple (local analysis case) ESD
  processing is implemented
• A TSelector prototype is being implemented
  (distributed analysis case)

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Framework Overview 2/2
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Alignment of volume(s)
Load space-points arrays with gt1 point in
volume(s) A
Apply accumulated alignment info (AliAlignObj)
for all space-points in volume(s) A and B

• Base method for aligning volumes
  AliAlignmentTracksAlignVolumes()
• What does it do?
• It aligns a volume A (set of volumes) w.r.t to
  another volume B (set of volumes)
• The input is two arrays (AB) of ints (volume
  unique IDs)
• The output is updated alignment info for the
  volume(s) A
• Note volume sets A and B can (partially) overlap
• Several predefined methods to align single
  volumes, layers are implemented

Fit space-point arrays (tracks) in volume(s) B
and extrapolate them to volume(s) A
Arrays with all space-points in volume(s) A
Arrays with track extrapol. points in volume(s) A
Calculate and minimize residuals in volume(s) A
Update alignment info (AliAlignObj)
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Track fitters

• Base class for track fitters AliTrackFitter
• Interface to space-point array being fitted
• Interface for getting the two space-points arrays
  (residuals)
• Abstract Fit() method
• Fits the track within user-defined volume(s)
• Prepare the arrays with residuals
• To do all fitters share some part of Fit()
  method
• ? move Fit() to the base class and define some
  methods inside as abstract
• Getters for fit quality information
• Current status
• AliTrackRiemanFitter implemented
• Ongoing development (MI and Cvetan)
• Interface to the ROOT TLinearFitter (Possibility
  to use Robust fitter)
• Linear fit, parabolic fit, Rieman fit with
  tilting angles ( for TRD), parabolic fit with
  tilting angles
• Interface to the Kalman fitter (AliExternalTrackPa
  ram)

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Track Residuals minimization

• Base class for residuals minimization
  AliTrackResiduals
• Two classes implemented
• Minuit based (AliTrackResidualsChi2)
• Fast linear minimization (AliTrackResidualsFast)
• Assume small mis-alignment rotation angles
• ? linear transformation
• Sufficient precision assuming angles mrad
• Interface to the TLinearFitter to be implemented
• Possibility of fixing parameters
• Robust fit

39
Alignment - status

• The misalignment implemented in the simulation
• The correction for the misalignment implemented
  in the reconstruction
• Test with misalignment on the level -1.5 mm and
  angular misalignment 0.6 degree made
• The performance of tracking with perfect
  alignment parameters almost the same as with
  ideal geometry
• First attempts to use alignment framework (real
  MC data) work in progress