Calibration and alignment Calibration and alignment softwaresoftware

Marian IvanovMarian Ivanov

OutlookOutlook

Impact of systematic effects on Impact of systematic effects on physical resultsphysical results

TPC calibration TPC calibration TPC alignmentTPC alignment

Statistical uncertainty Statistical uncertainty

R-Phi and Phi resolution for perfectly aligned and calibrated TPC (at the TPC R-Phi and Phi resolution for perfectly aligned and calibrated TPC (at the TPC entrance)entrance)

Given by the cluster position resolution ( divided by sqrt(Npoints))Given by the cluster position resolution ( divided by sqrt(Npoints)) At low momentum – influence of the multiple scatteringAt low momentum – influence of the multiple scattering

Misalignment of detectorsMisalignment of detectors

Linear misalignment can be detected Linear misalignment can be detected by our algorithm by our algorithm Statistic of 2000 tracks per sector Statistic of 2000 tracks per sector

(IROC+OROC) ( 72000 tracks) is big enough (IROC+OROC) ( 72000 tracks) is big enough to be on the level below statistical to be on the level below statistical uncertaintyuncertainty

Tested with stand-alone (fast) simulatorTested with stand-alone (fast) simulator Following slides – precision of the alignment Following slides – precision of the alignment

parameter determination for two different parameter determination for two different statistic sets statistic sets

Track fittingTrack fitting

AliRieman used for AliRieman used for track fittingtrack fitting Less than 1 s for Less than 1 s for

track fitting (20000 track fitting (20000 tracks)tracks)

Picture:Picture: Pt resolution for non Pt resolution for non

aligned sectorsaligned sectors Input misalignmentInput misalignment

2 mm in translation2 mm in translation 1 mrad rotation1 mrad rotation

1/ptrec-1/pt

Results –Rotation ZResults –Rotation Z

Left side – 2000 track samplesLeft side – 2000 track samples Right side – 5000 track samplesRight side – 5000 track samples

Left side – 2000 track samplesLeft side – 2000 track samples Right side – 5000 track samplesRight side – 5000 track samples

Translation XTranslation X

Left side – 2000 track samplesLeft side – 2000 track samples Right side – 5000 track samplesRight side – 5000 track samples

Translation YTranslation Y

Result (Pt residuals)Result (Pt residuals)

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

Alignment - ExBAlignment - ExB

ExB effect – simulated – linear dependence ExB effect – simulated – linear dependence expectedexpected Xshift = kx*(z-250) – kx=0.005Xshift = kx*(z-250) – kx=0.005 Yshift = ky*(z-250) - ky=0.005Yshift = ky*(z-250) - ky=0.005 The same in both sectorsThe same in both sectors

Alignment with tracks (2000 track samples)Alignment with tracks (2000 track samples) Systematic shifts in translation estimates Systematic shifts in translation estimates

(negligible in comparison with statistical error)(negligible in comparison with statistical error) X – 0.02 mm, Y – 0.08 mm, Z – 0.003 mmX – 0.02 mm, Y – 0.08 mm, Z – 0.003 mm

Systematic shift in rotation estimatesSystematic shift in rotation estimates Rz – 0.05 mrad, Ry – 0.006 mrad, Rx – 0.006 Rz – 0.05 mrad, Ry – 0.006 mrad, Rx – 0.006

mradmrad

Warning example - STAR - Warning example - STAR - TPC GridLeak distortionTPC GridLeak distortion

Dependence on field, track charge, location, luminosity Dependence on field, track charge, location, luminosity consistent with ion leakage at gated grid gapconsistent with ion leakage at gated grid gap

Hopefully not the case of Alice TPCHopefully not the case of Alice TPC

Alice ExB distortion Alice ExB distortion (M.Kowalski)(M.Kowalski)

Radial distortions at lower and outer TPC radius due to the nonuinformity of 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 magnetic field – E field perfectly aligned with B field at central membrane

Alice - Omega tau – 0.354 (E=400V/cm, B=0.5T)Alice - Omega tau – 0.354 (E=400V/cm, B=0.5T) Note :Note :

Non linearNon linear as function of z as function of z Phi dependencePhi dependence

Alice ExB distortion Alice ExB distortion (M.Kowalski)(M.Kowalski)

Azimuthal distortions at lower and outer TPC radius due to the Azimuthal distortions at lower and outer TPC radius due to the nonuinformity of magnetic fieldnonuinformity of magnetic field

Dy = 90cm x 0.0018 ~0.16 cm (Dy = 90cm x 0.0018 ~0.16 cm (STARSTAR reported magnitude of reported magnitude of correction on the level ~0.1 cm – nucl-ex/0301015)correction on the level ~0.1 cm – nucl-ex/0301015)

Systematic error - 4 times bigger than statististicalSystematic error - 4 times bigger than statististical

Alice ExB distortionAlice ExB distortion

InfluenceInfluence Systematic effect to the DCA resolutionSystematic effect to the DCA resolution

The distortion z and theta dependentThe distortion z and theta dependent For the first analysis the cut on the DCA has to be For the first analysis the cut on the DCA has to be

adjustedadjusted The influence on the pt resolution will be estimatedThe influence on the pt resolution will be estimated

Realistic magnetic field description needed (see next Realistic magnetic field description needed (see next slides)slides)

Track finding efficiency in TPC should be not be Track finding efficiency in TPC should be not be affected – (ExB distortion is a smooth function)affected – (ExB distortion is a smooth function)

Influence on the TPC-ITS track matchingInfluence on the TPC-ITS track matching

Tesla calculation (M.Losasso)currently in Aliroot

I = 30 kA

L3 field components

Measured field, I = 30 kA

(from ntuples of A.Morsch)

No corrections for possible probes misalignment applied

L3 field components

Drift velocityDrift velocity

Requirements (systematic error on the level of statistical error) Requirements (systematic error on the level of statistical error) Z resolution ~ 0.01 cmZ resolution ~ 0.01 cm vdrift precession ~ 0.4*10^-4vdrift precession ~ 0.4*10^-4

MeasurementsMeasurements Drift monitor – GOOFY Drift monitor – GOOFY ~ 10^-4 ~ 10^-4 Tracks crossing central membraneTracks crossing central membrane

STAR TPCSTAR TPC (Initial) drift velocities determined / monitored with lasers(Initial) drift velocities determined / monitored with lasers Automated updating of drift velocities (and initial T0) from laser Automated updating of drift velocities (and initial T0) from laser

runsruns Checked / fine-tuned by matching primary vertex Z position using east Checked / fine-tuned by matching primary vertex Z position using east

and west half tracks separately (Alice – algorithm tested by C.Cheskov)and west half tracks separately (Alice – algorithm tested by C.Cheskov) Ideally determined from track-matching to SVT (perpendicular drift), but Ideally determined from track-matching to SVT (perpendicular drift), but

requires all other calibs to be done already! (principle has been tested)requires all other calibs to be done already! (principle has been tested)

Electron attachmentElectron attachment

Electrons can be absorbed in the gas during the Electrons can be absorbed in the gas during the driftdrift

The probability to be captured by an O2 molecule The probability to be captured by an O2 molecule is 1% per 1 m drift per 1 ppm of O2 (NA49)is 1% per 1 m drift per 1 ppm of O2 (NA49)

Alice – expected oxygen content (ALICE MC)~ 5 Alice – expected oxygen content (ALICE MC)~ 5 ppmppm Should be achieved (Joachim) Should be achieved (Joachim)

InfluenceInfluence Non systematic effect to the position resolutionNon systematic effect to the position resolution Affects only statistical uncertainty by a factor Affects only statistical uncertainty by a factor

sqrt(absorbtion) and dEdx measurementsqrt(absorbtion) and dEdx measurement Does not affect multiplicity measurementDoes not affect multiplicity measurement

Gain calibrationGain calibration

The chip gains vary in range of 5%The chip gains vary in range of 5% Expected cluster position variation on the level of 0.05* Expected cluster position variation on the level of 0.05*

pad widthpad width Expected random behaviorExpected random behavior

The gain variation due to electrostatics (for The gain variation due to electrostatics (for example anode wire sagita) example anode wire sagita) does not affect the cluster position – (the effect of local does not affect the cluster position – (the effect of local

variation of gain is negligible as compared to cluster variation of gain is negligible as compared to cluster size)size)

Influence:Influence: Small influence on the pt resolution and efficiencySmall influence on the pt resolution and efficiency dEdx affected dEdx affected

TPC calibration: OutlookTPC calibration: Outlook

TPC calibration parametersTPC calibration parameters TPC calibration classesTPC calibration classes MI approach:MI approach:

The size of the calibration data in CDB (Condition The size of the calibration data in CDB (Condition Database) and in memory (during reconstruction) Database) and in memory (during reconstruction) dominated by the size of data for pad by pad. Everything dominated by the size of data for pad by pad. Everything else negligible. else negligible.

Store all data which can be used in the Store all data which can be used in the reconstruction, respectively which can used to indicate reconstruction, respectively which can used to indicate problems.problems.

Particularly the data from the sensors (voltages, currents, Particularly the data from the sensors (voltages, currents, temperature sensors) temperature sensors)

Offline code statusOffline code status

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, NoiseGainFactor, 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) InterfaceInterface

AliTPCCalROC(Int_t sector)AliTPCCalROC(Int_t sector) SetValue(padrow, pad, value)SetValue(padrow, pad, value) GetValue(padrow, pad)GetValue(padrow, pad)

Memory consumptionMemory consumption Npads x sizeof(value)Npads x sizeof(value)

0.5 million channels * sizeof(value)0.5 million channels * sizeof(value) 1D array for each sector1D array for each sector Mapping index – (padrow- row) using external map array class AliTPCRoc (1 per outer sector, 1 Mapping index – (padrow- row) using external map array class AliTPCRoc (1 per outer sector, 1

per inner sector)per inner sector)

TPC calibration parameters –per pad

ParameterParameter N. of N. of channelschannels UnitUnit SourceSource Update frequencyUpdate frequency

Gain factorGain factor 557568557568 Relative Relative Offline/HLTOffline/HLT RareRare

Time 0Time 0 557568557568 Relative ?Relative ? Offline/HLTOffline/HLT RareRare

Preamp-shaper Preamp-shaper widthwidth 557568557568 Relative ?Relative ? Offline/HLTOffline/HLT RareRare

NoiseNoise 557568557568 Relative Relative (sigma)(sigma) ?? RareRare

The difference between relative and absolute is in the data volumeThe difference between relative and absolute is in the data volume ~ 2MBy relative~ 2MBy relative ~ 8 MBy absolute~ 8 MBy absolute Current implementation in AliRoot – use floatsCurrent implementation in AliRoot – use floats

TPC conditions – per set of TPC conditions – per set of sensorssensors

ParameterParameterN. of N. of

channelchannelss

InformatioInformationn

SourcSourcee

Update frequencyUpdate frequency

Temperature probesTemperature probes

~4500 sensors ~4500 sensors on FEC, on FEC,

snesors on snesors on space space

frame? ?? frame? ?? Interface to Interface to

DCS DCS

Array of : ID, Array of : ID, position, samples position, samples (temparature) in (temparature) in timetime

DCS and ?DCS and ? Per runPer run

High voltageHigh voltage ??

Array of : ID, Array of : ID, samples (voltage samples (voltage and current) in and current) in timetime

DCSDCS Per runPer run

Drift voltage (VHV) Drift voltage (VHV) ??

Array of : ID, Array of : ID, samples (voltage samples (voltage and current) in and current) in timetime

DCSDCS Per runPer run

Gating voltages Gating voltages ?? Array of : ID, Array of : ID, voltagevoltage DCSDCS Per runPer run

Laser parametersLaser parameters Array of : ID, Array of : ID, position, anglesposition, angles ?? Per surveyer measurementPer surveyer measurement

The format should be defined as soon as possible The format should be defined as soon as possible Avoid problems with versioning Avoid problems with versioning Define queriesDefine queries

Data volume depends on the sampling frequencyData volume depends on the sampling frequency Can be reduced by fittingCan be reduced by fitting

The data format and functionality – Not TPC specificThe data format and functionality – Not TPC specific Common class should be definedCommon class should be defined Request for offline group presented (Hopefully someone will implement it)Request for offline group presented (Hopefully someone will implement it)

TPC calibration parameters – per TPC

ParameterParameterN. of N. of

channelchannelss

InformatioInformationn

SourcSourcee

Update frequencyUpdate frequency

Oxygen contentOxygen content 11 Samples in timeSamples in time DCSDCS Per runPer run

Drift velocity monitor Drift velocity monitor (Goofy)(Goofy) 22 Samples in timeSamples in time DCS?DCS? Per runPer run

Altro setupParameterParameter Data Data

volumevolumeSourcSourcee

Update frequencyUpdate frequency

Altro frequncyAltro frequncy 00

Altro acquisition windowAltro acquisition window 00

Moving average (on/off)Moving average (on/off) 00

Zerro suppresion Zerro suppresion (on/off)(on/off) 00

Tail cancelation (on/off)Tail cancelation (on/off) 00

TPC calibration parameters – per TPC

ParameterParameter Data Data volumevolume

SourcSourcee

Update frequencyUpdate frequency

Drift velocity map Drift velocity map (parameterization)(parameterization) ?? OffflineOfffline RareRare

Space charge map Space charge map ?? OfflineOffline RareRare

ExB correction map ExB correction map ?? OfflineOffline Per change of magnetic fieldPer change of magnetic field

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

TPC parameters for reconstruction

ParameterParameter Data Data volumevolume

SourcSourcee

Update frequencyUpdate frequency

Signal shape Signal shape parameterization parameterization (diffusion parameter)(diffusion parameter)

00 OffflineOfffline RareRare

Local error Local error parameterization ()parameterization () 00 OfflineOffline RareRare

Shuttle SchemaShuttle Schema AliShuttle AliShuttle – The Shuttle – The Shuttle

program manager. Organizes program manager. Organizes conditions data retrieval, conditions data retrieval, preprocessing and storing it preprocessing and storing it to CDB.to CDB.

AliShuttleConfig AliShuttleConfig – Interface to – Interface to the configuration stored into the configuration stored into LDAP serverLDAP server

AliDCSClient AliDCSClient – Provides DCS – Provides DCS API. Communicates with DCS API. Communicates with DCS AMANDAAMANDA server over TCP/IPserver over TCP/IP

AliShuttleTrigger AliShuttleTrigger – Interface – Interface totoDAQ LogBook and client to DAQ LogBook and client to DAQ “End of Run” DAQ “End of Run” notification servicenotification service

Offline calibration - StatusOffline calibration - Status

Calibration classes for pad parameters Calibration classes for pad parameters implemented implemented Default parameters stored in the databaseDefault parameters stored in the database Pad gain variation (+- 5%)Pad gain variation (+- 5%)

Used in simulation and reconstruction Used in simulation and reconstruction Noise, T0, and Preamp shaper width - will Noise, T0, and Preamp shaper width - will

be implemented soon in the simulationbe implemented soon in the simulation Typical variation of parameters needed as inputTypical variation of parameters needed as input

Alignment - OutlookAlignment - Outlook

Toy model results presented in Toy model results presented in previous slidesprevious slides

Short overview of reconstruction Short overview of reconstruction framework (Cvetan Cheskov)framework (Cvetan Cheskov)

Current developmentCurrent development Implement alignment algorithms inside Implement alignment algorithms inside

of AliRoot alignment frameworkof AliRoot alignment framework

Alignment frameworkAlignment framework

Space-points extraction and Space-points extraction and processing (filtering)processing (filtering)

Track fittingTrack fitting Track extrapolation pointsTrack extrapolation points Residuals minimizationResiduals minimization

Framework Overview 1/2Framework Overview 1/2

ESD filewith track

space-points

ESD filewith track

space-points

ESD filewith track

space-points

ESD filewith track

space-points

Tree withSelected

Space points

Build tree index

Alignment procedures

Local file

Reconstruction Reconstruction Reconstruction Reconstruction Phase I

Distributed

Local

Phase II

Phase III

Phase IV

Space-points retrieval Space-points retrieval (Phase I)(Phase I)

During the reconstruction, in between backward propagation and During the reconstruction, in between backward propagation and refitting:refitting: Loop over ESD tracks and sub-detectors (ITS,TPC,TRD,TOF,RICH):Loop over ESD tracks and sub-detectors (ITS,TPC,TRD,TOF,RICH):

Get cluster indexesGet cluster indexes Call trackers to get the space pointsCall trackers to get the space points Store the points inside the ESD trackStore the points inside the ESD track

The storage of space-points is controlled by The storage of space-points is controlled by AliReconstruction::SetWriteAlignmentData()AliReconstruction::SetWriteAlignmentData()

Unified AliESDtrack method of getting #clusters and their indexes:Unified AliESDtrack method of getting #clusters and their indexes: GetNcls(Int_t iDet) & GetClusters(Int_t iDet, UInt_t*)GetNcls(Int_t iDet) & GetClusters(Int_t iDet, UInt_t*)

Abstract method of AliTracker:Abstract method of AliTracker: GetTrackPoint(Int_t index, AliTrackPoint &p)GetTrackPoint(Int_t index, AliTrackPoint &p) Method implemented for ITS,TPC,TRD,TOFMethod implemented for ITS,TPC,TRD,TOF

Space points filtering (Phase Space points filtering (Phase II)II)

Filtering:Filtering: Take the ESD trees in a TChainTake the ESD trees in a TChain Select on ESD track parametersSelect on ESD track parameters Store selected space point arrays into tree Store selected space point arrays into tree

(in local file) for further analysis(in local file) for further analysis So far a simple (local analysis case) ESD So far a simple (local analysis case) ESD

processing is implementedprocessing is implemented A TSelector prototype is being A TSelector prototype is being

implemented (distributed analysis case)implemented (distributed analysis case)

Framework Overview 2/2Framework Overview 2/2

Read alignmentobjects

CDBIterations loop(user-defined)

Loop over volumes(user-defined)

Update alignmentobjects

Align volume(s)

CDB

Fit tracks

Minimize residuals

File

Alignment of Alignment of volume(s)volume(s)

Base method for aligning volumes: Base method for aligning volumes: AliAlignmentTracks::AlignVolumes()AliAlignmentTracks::AlignVolumes()

What does it do?What does it do? It aligns a volume A (set of volumes) It aligns a volume A (set of volumes)

w.r.t to another volume B (set of w.r.t to another volume B (set of volumes)volumes)

The input is: two arrays (A&B) of The input is: two arrays (A&B) of ints (volume unique IDs)ints (volume unique IDs)

The output is: updated alignment The output is: updated alignment info for the volume(s) Ainfo for the volume(s) A

Note: volume sets A and B can Note: volume sets A and B can (partially) overlap(partially) overlap

Several predefined methods to align Several predefined methods to align single volumes, layers are single volumes, layers are implementedimplemented

Load space-points arrayswith >=1 point in volume(s) A

Apply accumulated alignment info(AliAlignObj) for all space-points

in volume(s) A and B

Fit space-point arrays (tracks)in volume(s) B and extrapolate

them to volume(s) A

Arrays with allspace-points

in volume(s) A

Arrays with trackextrapol. pointsin volume(s) A

Calculate and minimizeresiduals in volume(s) A

Update alignment info (AliAlignObj)

Track fittersTrack fitters Base class for track fitters – AliTrackFitter:Base class for track fitters – AliTrackFitter:

Interface to space-point array being fittedInterface to space-point array being fitted Interface for getting the two space-points arrays (residuals)Interface for getting the two space-points arrays (residuals) Abstract Fit() method:Abstract Fit() method:

Fits the track within user-defined volume(s)Fits the track within user-defined volume(s) Prepare the arrays with residualsPrepare the arrays with residuals To do: all fitters share some part of Fit() methodTo do: all fitters share some part of Fit() method

move Fit() to the base class and define some move Fit() to the base class and define some methods inside as abstractmethods inside as abstract Getters for fit quality informationGetters for fit quality information

Current statusCurrent status AliTrackRiemanFitter implementedAliTrackRiemanFitter implemented

Ongoing development (MI and Cvetan)Ongoing development (MI and Cvetan) Interface to the ROOT TLinearFitter (Possibility to use “Robust” fitter)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 anglesLinear fit, parabolic fit, Rieman fit with tilting angles ( for TRD), parabolic fit with tilting angles Interface to the Kalman fitter (AliExternalTrackParam)Interface to the Kalman fitter (AliExternalTrackParam)

Track Residuals minimizationTrack Residuals minimization

Base class for residuals minimization – Base class for residuals minimization – AliTrackResiduals:AliTrackResiduals:

Two classes implemented: Two classes implemented: Minuit based (AliTrackResidualsChi2)Minuit based (AliTrackResidualsChi2) Fast linear minimization (AliTrackResidualsFast):Fast linear minimization (AliTrackResidualsFast):

Assume small mis-alignment rotation angles:Assume small mis-alignment rotation angles:

linear transformationlinear transformation Sufficient precision assuming angles ~mradSufficient precision assuming angles ~mrad

Interface to the TLinearFitter to be implementedInterface to the TLinearFitter to be implemented Possibility of fixing parametersPossibility of fixing parameters Robust fitRobust fit

z

y

x

rr

1

1

1'

Alignment - statusAlignment - status

The misalignment implemented in the The misalignment implemented in the simulationsimulation

The correction for the misalignment The correction for the misalignment implemented in the reconstructionimplemented in the reconstruction Test with misalignment on the level +-1.5 mm and Test with misalignment on the level +-1.5 mm and

angular misalignment 0.6 degree madeangular misalignment 0.6 degree made The performance of tracking with perfect alignment The performance of tracking with perfect alignment

parameters – almost the same as with ideal geometryparameters – almost the same as with ideal geometry First attempts to use alignment framework First attempts to use alignment framework

(“real MC” data) – work in progress (“real MC” data) – work in progress