Post on 02-Jan-2016
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 1
Software Alignment of the CMS Software Alignment of the CMS Tracker Tracker
V. KarimV. Karimääki / HIPki / HIP
Workshop on B/Tau Physics at the LHCWorkshop on B/Tau Physics at the LHCHelsinki, May 30 - June 1, 2002Helsinki, May 30 - June 1, 2002
Topics:Topics: General considerationsGeneral considerations StrategiesStrategies AlgorithmsAlgorithms Helsinki auto-alignment algorithmHelsinki auto-alignment algorithm Concluding remarks Concluding remarks
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 3
Alignment processes - hardware + softwareAlignment processes - hardware + software
Precisionassembly
Initial positions(modules)
Monitoring information
Positionscorrected
by monitoringAlignment by
tracks
Surveys in situ
For once
‘Final’calibratedpositions
Once a year …?
‘Continuous’?
For every shot?
Signal
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 4
Detector alignment by tracks - why, howDetector alignment by tracks - why, how
WhyWhy
Precision after assembly and optical surveys 0.1 - 0.2 mm (?)Precision after assembly and optical surveys 0.1 - 0.2 mm (?) Needs about 0.5 * hit resolution i.e. 5 - 30 Needs about 0.5 * hit resolution i.e. 5 - 30 mm Magnetic field effects, temperature effectsMagnetic field effects, temperature effects
HowHow Utilising natural smoothness of particle trajectoriesUtilising natural smoothness of particle trajectories
Using high pUsing high pT T trackstracks
Misalignments systematic offsets of hits from trajectoriesMisalignments systematic offsets of hits from trajectories
Software algorithm(s) to Software algorithm(s) to reduce systematic offsetsreduce systematic offsets by by
correcting the detector positionscorrecting the detector positions
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 5
Elementary alignment ‘manually’Elementary alignment ‘manually’
1D EXAMPLE
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 6
Importance of alignment precisionImportance of alignment precision
Example:Example:
Error in local u-coord due to tilt Error in local u-coord due to tilt
u ~ u tanu ~ u tan
u = 10 u = 10 mm = 45= 45oo
u = 5 cmu = 5 cm
Implies:Implies:
= 0.2 mrad = required angular precision= 0.2 mrad = required angular precision
u
Tilt angle
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 7
Algorithm developmentAlgorithm development
Formulations, basic tools:Formulations, basic tools: Dependence of correction parameters on residuals - can be Dependence of correction parameters on residuals - can be
complicatedcomplicated 2 2 minimization, Kalman Filter techniques, linear algebra - standard minimization, Kalman Filter techniques, linear algebra - standard
techniquestechniques misalignment tools (for development and validation)misalignment tools (for development and validation) track reconstructiontrack reconstruction
Algorithms validation:Algorithms validation: Monte Carlo simulation - comparison of known misalignments with Monte Carlo simulation - comparison of known misalignments with
corrections obtained by the algorithm - pull valuescorrections obtained by the algorithm - pull values Test-beam data - improvement of hit resolutions, trajectory qualityTest-beam data - improvement of hit resolutions, trajectory quality Alignment contest!Alignment contest!
referee referee to prepare recHit data set with misaligned detectorto prepare recHit data set with misaligned detector the algorithms should find the misalignments within errorsthe algorithms should find the misalignments within errors
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 8
CMS misalignment toolCMS misalignment toolHelge Voss
Britta SchweringTapio Lampen
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 9
Misalignment tool use casesMisalignment tool use cases
Study of misalignment effects on reconstructionStudy of misalignment effects on reconstruction Development and testing of alignment algorithmsDevelopment and testing of alignment algorithms
Movement rods/wedges x = y = z =1000 m:
Z events
Helge Voss:
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 11
Hierarchy and application strategyHierarchy and application strategy
Hierarchy of alignment corrections:Hierarchy of alignment corrections:-full detector-full detector -barrel, F/B detectors-barrel, F/B detectors -barrel layers, forward disks-barrel layers, forward disks -barrel rods, forward wedges-barrel rods, forward wedges -detector modules (assumed planar)-detector modules (assumed planar)i.e. factorization of the problem when working on the alignment i.e. factorization of the problem when working on the alignment
Alignment correction mappings:Alignment correction mappings:-rotation, translation, 3+3=6 parameters per unit-rotation, translation, 3+3=6 parameters per unit-sag, twist, 2 or 3 parameters typically per unit (not for modules)-sag, twist, 2 or 3 parameters typically per unit (not for modules)
Application strategy:Application strategy:Compute and transform all global corrections down to the lowest Compute and transform all global corrections down to the lowest
level, i.e. to the detector moduleslevel, i.e. to the detector modules
Aligned reconstruction geometry = ideal geometry + wafers Aligned reconstruction geometry = ideal geometry + wafers position/orientation correctionsposition/orientation corrections
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 12
Software alignment strategiesSoftware alignment strategies
Distinguish:Distinguish:
1) Alignment start-up (launched at Day 1)1) Alignment start-up (launched at Day 1) input is ‘best geometry’ by assembly, survey and monitoringinput is ‘best geometry’ by assembly, survey and monitoring ‘‘large’ correctionslarge’ corrections steep (human) learning curvesteep (human) learning curve tedious, time takingtedious, time taking
2) Alignment calibrations (at regular intervals)2) Alignment calibrations (at regular intervals) input is previous best alignment + monitoring informationinput is previous best alignment + monitoring information repetition rate 1 day or more (experience only tells)repetition rate 1 day or more (experience only tells) ‘‘small’ correctionssmall’ corrections learning curve levelling off learning curve levelling off might become routine-likemight become routine-like yet always room for improvements (algorithms, statistics, …)yet always room for improvements (algorithms, statistics, …)
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 13
Possible schedule for alignment start-upPossible schedule for alignment start-up
Preparations:Preparations: Work out estimates of alignment errors (important for pattern Work out estimates of alignment errors (important for pattern
recognition)recognition) Further tuning of track reconstructionFurther tuning of track reconstruction Using isolated particles (high p_T muons)Using isolated particles (high p_T muons)Work inside out:Work inside out: Semi-independent alignment of Pixel detectorSemi-independent alignment of Pixel detector
tracks curvature by full tracker, especially for 2-layer Pixeltracks curvature by full tracker, especially for 2-layer Pixel vertex constraint important (therefore start with Pixel)vertex constraint important (therefore start with Pixel) hits only for Pixel independent alignmenthits only for Pixel independent alignment determines the coordinate systemdetermines the coordinate system given elements need to be fixed (simulations will help to tell us)given elements need to be fixed (simulations will help to tell us)
Continue with TIB, TOB, …Continue with TIB, TOB, … Matching between Tracker partsMatching between Tracker parts Matching with muon chambersMatching with muon chambers
Iteration cyclesIteration cycles
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 14
Sagitta and spurious sagittaSagitta and spurious sagitta
Sagitta: largest distance cord to arc
Spurious sagitta: change due to systematic errors in hit position =a measure of misalignments
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 15
Curvature accuracy for Pixel alignmentCurvature accuracy for Pixel alignment
SPURIOUS SAGITTA
In Pixel
In T
rack
er
• sagitta is proportional to L2
• consider 2-layer Pixel• sagitta error (Pixel) / sagitta error (Tracker) ~ (7.2/105)2 ~ 0.005
We conclude:
1 mm sagitta errordue to misaligmentsin full Tracker reflectsonly 5 m sagitta errorin 2-layer Pixel
We get precise enoughcurvature determinationfrom misaligned Trackerfor (semi)independentPixel alignment
Can we align Pixel independently of the rest of the Tracker on Day 1?Yes, if we can obtain precise enough curvature using full Tracker:
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 17
Candidates for alignment algorithms - 1Candidates for alignment algorithms - 1
Alignment by Kalman Filter methodAlignment by Kalman Filter method Fruhwirth et al., CMS Note-2002/008Fruhwirth et al., CMS Note-2002/008 uses annealing to avoid secondary minimauses annealing to avoid secondary minima 3-parameter alignment tested with simulated test-3-parameter alignment tested with simulated test-
beam like setupbeam like setup
Helsinki auto-alignment methodHelsinki auto-alignment method 22 minimization formalism minimization formalism iterative, several passes over given dataiterative, several passes over given data up to 6 parameters per moduleup to 6 parameters per module successfully applied to real test-beam data (silicon successfully applied to real test-beam data (silicon
telescope) with 5 parameter alignmenttelescope) with 5 parameter alignment mathematics of the algorithm are simplemathematics of the algorithm are simple involves small matricesinvolves small matrices ORCA implementation under workORCA implementation under work
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 18
Candidates of alignment algorithms - 2Candidates of alignment algorithms - 2
H1 method (Gabathuler/PSI)H1 method (Gabathuler/PSI) used for H1 vertex detectorused for H1 vertex detector algorithm (implicit vertex constraint):algorithm (implicit vertex constraint):
all pairs of tracksall pairs of tracks minimizing sum of squared distances in space between minimizing sum of squared distances in space between
all track pairsall track pairs mathematics of the algorithm complicatedmathematics of the algorithm complicated
Blobel method (Raupach/Aachen)Blobel method (Raupach/Aachen) 22 solution of a very large number of parameters solution of a very large number of parameters CMS/Aachen people ...CMS/Aachen people ...
A large number of algorithms exist, more than A large number of algorithms exist, more than one per experiment, experiment specificone per experiment, experiment specific
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 19
Brief description of Helsinki algorithm
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 20
Helsinki auto-alignment - 1Helsinki auto-alignment - 1
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 21
Helsinki auto-alignment - 2Helsinki auto-alignment - 2
Workshop on B/Tau Physics, Helsinki 30.5.-1.6.2002 V. Karimäki, HIP 22
Concluding remarksConcluding remarks
Aiming at:Aiming at:Toolkit for tracker alignment with tracks = auto-alignment toolkitToolkit for tracker alignment with tracks = auto-alignment toolkitProviding an effective (default) algorithm Providing an effective (default) algorithm Stand-alone version for simulation of telescope-like setupStand-alone version for simulation of telescope-like setupTracker auto-alignment simulation in ORCA framework Tracker auto-alignment simulation in ORCA framework Status:Status:Mathematical formulation of an effective algorithm: derived, testedMathematical formulation of an effective algorithm: derived, testedUsed successfully in test-beam environment Used successfully in test-beam environment (CMS NOTE 2000/013)(CMS NOTE 2000/013)
OO modeling and coding of the 'core' classes: first iterationOO modeling and coding of the 'core' classes: first iterationSimplified telescope-like alignment simulation: first resultsSimplified telescope-like alignment simulation: first resultsInterface with ORCA: startedInterface with ORCA: startedFuture work:Future work:Development of ORCA interfaceDevelopment of ORCA interfaceStudies of auto-alignment for chosen parts of the TrackerStudies of auto-alignment for chosen parts of the TrackerStudies of using constraints (beam, vertex, $Z^0$-kinematics,\dots)Studies of using constraints (beam, vertex, $Z^0$-kinematics,\dots)Studies of correlated modules alignment Studies of correlated modules alignment etc...etc...