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Tracker Alignment Strategies for ATLAS and CMS. ATLAS & CMS Alignment. Muge Karagoz Unel On behalf of ATLAS and CMS Alignment Groups 12 th April 2007 UK HEP Forum – LHC Startup Cosener\'s House, Abingdon. Will try to cover… Motivations for alignment The experiments and detectors

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tracker alignment strategies for atlas and cms

Tracker Alignment Strategies for ATLAS and CMS

ATLAS & CMS Alignment

Muge Karagoz Unel

On behalf of ATLAS and CMS Alignment Groups

12th April 2007

UK HEP Forum – LHC Startup

Cosener\'s House, Abingdon

Will try to cover…

Motivations for alignment

The experiments and detectors

Alignment Performances

The current status and plans for early data

Disclaimer: Will concentrate mostly on inner tracker alignment and make use of ATLAS.

Note: most trigger plans & early physics issues will be described by the other speakers.


ATLAS & CMS Alignment

the prerequisites
the Prerequisites
  • General purpose LHC detectors ATLAS & CMS need to cope with demands of LHC physics programme requirements
  • Precision and accuracy is crucial for EWK and new physics
    • particle ID at ultra high energies
    • b-tagging for top and Higgs physics
    • W-mass measurement (one of the most challenging!)
  • Design parameters from ATLAS:
    • Calorimetry
      • s(E)/E = 11.4% E, for electrons
    • Tracking
      • s(pT/pT) = 20% , for muons of 500 GeV

ATLAS & CMS Alignment

  • Examples from ATLAS tracking:
    • localalignment < 10μm so as not to degrade intrinsic resolution > 20 %
    • B-field to 0.1% locally
    • material globally to 1%
the atlas detector
the ATLAS Detector

Barrel m-spectrometer (MDT) with 4T toroid

22 m

ATLAS & CMS Alignment

46 m

Inner tracker (ID) (TRT+silicon)

2T solenoid

Endcap m-spectrometer (MDT+CSC)

with Endcap toroid

the cms detector
the CMS Detector

Barrel m (DT)

15 m

ATLAS & CMS Alignment

22 m

Inner tracker (silicon)

4 Tesla solenoid

Endcap m (CSC)

the challenge atlas id is big



(3 layers+3 disks)

SCT endcaps: 9 disks

SCT barrels: 4 layers

the Challenge: Atlas ID is BIG

5.4 m

ATLAS & CMS Alignment

6 DoF/module:

3 translations

& 3 rotations

Silicon total DoF = 6x 5832 = 34992!

TRT total DoF = 7x96 + 6x56= 1008

Alignment challenge!

and cms currently the most silicon

Outer Barrel (TOB)

6 layers 5208 modules

Endcap (TEC)

9 discs, 4-7 rings,

6400 modules

r (mm)


blue = double-sided‏

red = single-sided


z (mm)

Inner Barrel (TIB)

4 layers, 2724 modules

Inner Disc (TID)

3 discs, 3 rings, 816 modules

and CMS=Currently the Most Silicon

206 m2 of Si

pixels not shown

ATLAS & CMS Alignment


Strip pitch 80-205 µm

σ ≈ 23-60 µm, 230-520 µm

15148 modules

Pixels size 100x150 µm

σ ≈ 10x15 µm

1900 modules

atlas id module specifications




ATLAS ID Module specifications

ATLAS & CMS Alignment

  • Pixel detectors: real 2-D readout
    • Size 50400 m with 14115(60) m resolution.
  • SCT modules: double-sided strip detectors with 1-D binary RO/side (768 strips).
    • Strips pitch of 80 m giving 23 m resolution.
    • Stereo-angle of 40 mrad gives 580 m resolution in rz direction.
    • Mounting precision ~ 100 m
    • end-cap modules are in wedged shape
  • TRT has 300k straw tubes
    • Size 4mmx740mm, resolution 170m (perp to wire)
alignment generalities
Alignment Generalities
  • Alignment is determination of
    • Sensitive detector position, orientation (6 parameters)
    • module deformation due to temperature, magnetic field,

material load

      • For ex., shrinkage of muon detectors of order of 1cm with B-field on!
  • Consists of 4 components
    • Assembly knowledge: construction precision and surveys, for initial position corrections and errors
    • Online monitoring and alignment: lasers, cameras, before and during runs
    • Offline track-based alignment: using physics and cosmic data track residual information
    • Offline monitoring and alignment: using track and particle ID parameters
  • Challenges for the track-based alignment
    • Both detectors have large number of DoF to solve for.
    • Insensitivity to weak modes w/o additional constraints from data

ATLAS & CMS Alignment

prospects for lhc beams
Prospects for LHC Beams

Parasitic collisions with wide range of interaction z-point

ATLAS & CMS Alignment

With the recent magnet problems, not sure will happen in time or happen at all… 

expected event rates
Expected Event Rates

F. Gianotti (ICHEP 2006)

Not much of anything else other than min bias and QCD jets

ATLAS & CMS Alignment

Physics Run 2008 @ 14 TeV, L~1032…33

Large statistics of high pt muons within few weeks!

Trigger studies are underway by both experiments

who ordered misalignment
Who Ordered Misalignment?
  • Misalignment is due to
    • Precision of assembly
    • Stress from magnetic field or thermal stress
    • Changes due to humidity, …
  • Misalignment is time dependent! and when and how much the time the parts will move around is unknown.

Misalignment studies:

  • Ideal geometry
    • No misalignment
  • Short-term (<1 fb-1)‏
    • First data taking
    • Hardware alignment used
  • Long term (1-5 fb-1)‏
    • First alignment with high-statistics tracks, for first physics analysis
  • Final alignment
    • Do not deteriorate detector resolution

ATLAS & CMS Alignment

Martin Weber, CMS

misalignment bsm searches

C = 0.01 (coupling constant)

First data

C =0.1

Long term

Dimuon Mass

Misalignment: BSM Searches

Example for ~early LHC physics: Resonances in Di-Muons

5  discovery reach for RS gravitons

Would need about 50% less data if optimal alignment!

ATLAS & CMS Alignment

Georg Steinbruck, CMS

basic tasks and handles

CMS material corrections

Basic Tasks and Handles
  • First days of data-taking: Figuring out anomalies: Calibration and alignment!
  • First goal: working tracking reconstruction!
    • Hit errors, Dead/noisy hardware (and software!) components
    • Realistic simulation corrections, material effects
    • Match with muon chambers and calorimeters
    • Absolute momentum scale (using known resonances)
    • Tracking efficiency (dimuons from J/, Upsilon, Z)

ATLAS & CMS Alignment

basic tasks and handles1
Basic Tasks and Handles
  • Alignment Handles:
      • Cosmic rays
      • Beam halo muons, beam gas events
      • Isolated muons from b decays, isolated

tracks from MB events

      • W, Z resonances
      • Note: Collision tracks and cosmics populate different parts of global covariance matrix of alignment -> make complete datasets
  • Dedicated data streams
  • Study timescales for detector movements and finalize the Software and Computing Model accordingly for long-term alignment
  • Align first large structures, then sensors at high statistics or limit ourselves to limited number of DoF



Pilot runs




ATLAS & CMS Alignment

cosmics beam halo
Cosmics & Beam Halo

Provided that they do not harm sensitive detector material!

ATLAS: Trigger using TileCal, current trigger rates ~ 10Hz

cosmics during commissioning, do not expect stable alignment until global cosmics (~fall 2007).

ATLAS & CMS Alignment

atlas id track based alignment
Intrinsic alignment of Silicon and TRT, Si+TRT, all rely on minimizing residuals

Global 2:

minimization of 2 fit to track and alignment parameters

6 DoF, correlations managed, small number of iterations

Inherent challenge of large matrix handling and solving

Local 2 :

similar to global 2, but inversion of 6x6 matrix/module

6 DoF, no inter-module or MCS correlations

large number of iterations

Robust Alignment:

weighted residuals, z & r overlap residuals of neighbouring modules

2-3 DoF, many iterations, no minimization

All algorithms implemented within ATLAS framework, sharing common tools

Able to add constraints from physics & external data <- crucial!




Alignment Algorithm

Iteration until convergence



Final Alignment Constants

ATLAS ID Track-based Alignment

ATLAS & CMS Alignment

Performances on subsequent slides



Intrinsic measurement error + MCS



Key relation!

ATLAS Global 2 Approach

Method consists of minimizing a giant 2resulting from a simultaneous fit of all particle trajectories and alignment parameters:

Use the linear expansion (assume all second order derivatives negligible). Track fit solved by:

ATLAS & CMS Alignment

alignment parameters given by:

Equivalent to Millepede approach from V. Blobel for CMS

cms track based id alignment
CMS Track-based ID Alignment
  • Three different algorithms implemented in CMS reconstruction software
  • Millepede-II:
    • Global 2 formalism
    • Replaces original Millepede (brute matrix inversion) with iterative solver
    • Most promising approach to CMS problem for long-term scenario
  • HIP Algorithm:
    • Local 2, inversion of 6x6 matrix/module
    • correlations through iterations
  • Kalman Filter:
    • Iterative, based on Kalman filter update
    • Converges slower
  • Similar to ATLAS, can add constraints from physics & external data

ATLAS & CMS Alignment

misaligment studies on pixels with HIP

solving large degrees of freedom





Inversion fails


~log10 |AA-1 -I|



0 20000 40000 60000 80000 N

Solving Large Degrees of Freedom
  • Challenge: CMS and ATLAS have large systems to solve (100k & 36k DoF)
  • Formalisms require novel techniques
  • Limiting factors:
    • Size: Full ID needs O(10GB) for handling the alignment matrices
    • Precision: Matrices can have large condition numbers (compete with machine prec.)
    • Execution time: Single-CPU machines with non-optimized libraries take hours

ATLAS: Currently solving using 64-bit //-computing ⇒ full system was possible only last year!

    • Solving full pixel (12.5k DoF) on 16 nodes takes only 10mins (7hrs on Intel P4, diagonalization)
    • Work ongoing for improvements: already implemented MA27 in Athena:

takes 7sec for 6180 DoF, single-CPU


    • Millepede-II using MinRes was shown to

solve 12k DoF in 30sec in single-CPU!

  • Generally, issues depend on the sparsity

of matrices and other factors.

Things get really complicated!

(During datataking, a few mins performance differences

in solvers may not be our bottleneck problem!)

ATLAS & CMS Alignment

weak distortional modes
“Weak” Distortional Modes..

Problem: Certain transformations leave 2unchanged. Need extra handles to tackle these:

  • Requirement of a common vertex (VTX constraint),
  • Constraints on track parameters or vertex position (external tracking, calorimeters, resonant mass, ...)
  • External constraints (hardware systems, mechanical constraints, …).

Easily incorporated in the formalisms (for ex, global 2)

ATLAS & CMS Alignment

  • dependent sagitta


  • dependent sagitta

“Global twist”




VTX constraint

radial distortions





Mass constraints, cosmics, E/p, charge dep

more on weak global modes
More on Weak Global Modes

Example “lowest modes” in PIX+SCT

Global Freedom ignored

ATLAS & CMS Alignment

  • Weak modes contribute to the lowest part of the eigenspectrum.
  • These deformations lead directly to biases on physics (systematic effects).
  • Such global effects already under study (lots of preliminary results, have no time to show all, so will sample in next pages!)
atlas csc challenge
ATLAS “CSC” Challenge

Currently using “multimuons” data with a realistic as-built geometry to align the ID algorithms

Aim to test performance and understand needs for real data conditions

Level of applied misalignments:

  • Modules = Level 3
  • Layers = Level 2 (barrel layers or disks)‏
  • Subdetectors = Level 1 (whole barrel or EC)‏

Expected misalignments:

  • Modules: 30-100 µm, 1mrad
  • Layers: 100 µm
  • Silicon Barrels & EC: Up to few mm

From detector assembling and installation:

Misalignments largest on L1 and smallest on L3

⇒ Alignment strategy: L1 ⇒ L2 ⇒ L3

ATLAS & CMS Alignment

Bs studies with misalignment: 14% less candidates reconstructed (B. Epp)

Same misalignments are also used to check physics performances

csc algorithm performances


1st Iteration

8th Iteration

Input Misalignment

Robust Alignment

CSC: Algorithm Performances

Check if the algorithms converge and improve residuals

Check if efficiency and track parameters improve

Global chi2

ATLAS & CMS Alignment

Local chi2


csc welcome to the real world
CSC: Welcome to the Real World

Improved residuals is only a part of the story..

Are we able to see systematic effects (mostly weak modes) after alignment? Yes, as biases in track parameters

As the algorithms cannot fix these alone, use additional constraints

Transverse translations detected and already incorporated in algorithms: vertex/beam spot fit. Especially to be studied in pilot run.

Also apparent in pT, mass and charge-dep. E/P handles

ATLAS & CMS Alignment

atlas id alignment ctb performances

8 (-1) SCT


(1 dead)







After Robust


ATLAS ID Alignment: CTB Performances
  • First real data from ID at H8 beam in 2004
  • Large statistics of e+/e- and  (2-180 GeV)

(O(105) tracks/module/E), B-field on-off runs

  • Limited layout (6 PiX, 8 SCT, 6 TRT)
  • Results from various algorithms are being combined: reached a level sensitive to effects at a few microns!

ATLAS & CMS Alignment

Overall residual resolution obtained: Pix residual sigma ~10m, SCT ~ 20m

Excellent agreement

atlas sr1 cosmics performances
Surface (SR1) runs in spring 2006: ~400k Barrel cosmics recorded (22% of SCT, 13% of TRT)

No B-field! No momentum! MSC important ~<10 GeV, need to deal with larger residuals than CTB

Average Unbiased

Residual Sigma [mm]


Global 2

Local 2

Helen Hayward

ATLAS SR1 Cosmics: Performances

Excellent assembly precision!



ATLAS & CMS Alignment

Global 2

Largest sample used ~200k tracks

TRT+SCT: relative twist of SCT and TRT of 0.2 mrad

atlas id optical alignment fsi









Barrel SCT

Spatial frequency



End-cap SCT


ATLAS ID optical alignment (FSI)
  • Frequency Scanning Interferometry: Geodetic grid of 842 simultaneouslength measurements (precision <1m ) between nodes on SCT support structure.
  • Grid shape changes determined to <10m in 3D.
  • Time + spatial frequency sensitivity of FSI complements track based alignment:
    • Track alignment average over ~24hrs+.

high spatial frequency eigenmodes, “long” timescales.

    • FSI timescale (~10mins)

low spatial frequency distortion eigenmodes -> weak global modes!

  • Software principles already studied, implementation to be finalized!

ATLAS & CMS Alignment

atlas fsi on detector

Distance measurements between grid nodes precise to <1 mm

ATLAS FSI on detector

ATLAS FSI barrel is mostly serviced and cabled in the pit (only waiting for endcap for final touch).

FSI will be used intensively before and during the early runs and the track-based alignment and FSI interplay will be tested. Stability of the detector will tell how frequent data needs taken during normal operation.

ATLAS & CMS Alignment

atlas m spectrometer alignment





53 mm

Spot target

ATLAS m-spectrometer Alignment
  • Spectrometer: 1252 MDT chambers

(708 Barrel, 544 Endcap)

Muon track will be measured

with 3 drift tube chambers(~18-20 layers)


10% pT resolution on 1TeV muon:

sagitta of 500 μm measured with 50 μm accuracy

  • muon chambers must be aligned to 30 μm

(Intrinsic resolution of a channel: 80 μm)

When Toroid is on, chambers will move by several mm => Optical alignment needed.

hourly geometry changes expected.

ATLAS & CMS Alignment

MDTs monitored for 9 chamber distortions, eg, elongation, sagging,.. 3 system with 3-point principle

Florian Bauer, 4/9/2006, LHC Alignment Workshop

atlas m alignment status



ATLAS m alignment Status
  • Optical alignment software validated at CTB, hardware installation underway.
  • 2 softwares: ASAP (barrel) and AraMyS (endcap)
    • Combine optical information with straight/High Pt tracks in global fit
    • Describe the 9 chamber deformations in the fit => 6 + 9 DoFs per chamber.
    • Handle up to 10k DoFs both in the Barrel and Endcap
  • Run online with a latency of 24h.

=> robust algorithms, automated dataflow, monitoring, use of Databases as IO

  • For alignment&calibration, a special L2 trigger data stream is being setup
  • Misalignment studies show that the algorithms see the misalignments
  • Obtaining the required alignment is shown to take about 1/2 day, assuming parallel inner/outer chambers (ATLAS T&P week).

ATLAS & CMS Alignment

cms hardware alignment system
CMS Hardware Alignment System
  • Components
    • Internal muon alignment
      • barrel (all chambers)
      • endcap (selected)
    • Internal tracker alignment (LAS)
      • TEC w.r.t. TOB;
      • TEC w.r.t. TIB.
    • Muon w.r.t. tracker (Link system)
  • Specifications
    • Tracker structures ~10-100μm
    • Muon chambers at ~ 100μm
    • Muon vs tracker ~ 100μm
  • LAS:
    • monitor selected modules to get global alignment
    • 16+10+12 beams in total
    • Beams treated like tracks

ATLAS & CMS Alignment

cms hardware alignment system1



Transfer plate

Note: only small

sample of analog

sensors shown



CMS Hardware Alignment System
  • CMS LAS has been used in parts successfully during reconstruction and is installed at the test centre at CERN for tests
  • Treats beams as tracks: nothing but another straight track fit!
  • Full CMS hardware is 40k parameters
  • Lots of software challenges, similar to track-based algorithms

ATLAS & CMS Alignment


surveying the detectors
Surveying the Detectors

ATLAS SCT Barrel photogrammetry survey was done in 2006 at SR1

measurements tell two faces appear to be rotated in opposite directions, hinting at twists of the complete barrel (order of 100 μm).

ATLAS & CMS Alignment

CMS results from including survey constraints in alignment shows improvement in residuals (similarly in ATLAS)

atlas cms tracker status


CMS outerbarrel slice test (Feb07)


ATLAS & CMS Tracker Status


  • Barrel tracker (except pixel) integrated in the pit and soon will take cosmics data. Pixels and endcap taking cosmics at surface. Endcaps installation end of may, pixels will go in mid-june.


  • Strip tracker complete and its 1/8th is being read out. August onward, it will be completely in the pit and will take cosmics from mid-october. Installation plans for pixel is to be ready for data taking in 2008.

ATLAS & CMS Alignment

Both experiments have similar challenges and ideas for alignment, with different choice of optical alignment systems.

Both experiments’ track-based alignment software are in place, heavily tested, and providing proof of principles. They are at the cutting edge of today’s computing resources.

We have been looking at real data already! Misaligned simulation studies underway.

A lot has been learned, fixed, improved, but there is a lot more to do!

We will be ready for collision data, however, full scalability needs to be proven with real collision data conditions: datastream from triggers, huge data samples, computing power, GRID-readiness, etc.

The first collisions will be useful to exercise further the tools and understand the actual needs (time-scales, online monitoring, ...) rather than providing the final set of constants.

Thankfully we do not need to reinvent most of the wheel, previous colliders suffered from similar symptoms.

We need to be prepared for the unexpected, many issues upstream and downstream of alignment algorithms will exist and need to be understood: we cannot expect to obtain final module level alignment from day 1, but will likely nail down the global structures quickly.


ATLAS & CMS Alignment

Please Stay Tuned!

Ian Tomalin (CMS/RAL) for pointing me to the CMS information and answering my questions.

Pawel Bruckman (ATLAS/Oxford)

Jochen Schieck (ATLAS/MPI Munich)

Andrea Bocci (ATLAS/Duke)

Maria Costa (ATLAS/Valencia)

Numerous figures/slides borrowed from various talks, especially from the LHC alignment workshop of last fall.

Of course, thanks to all the alignment and detector teams of both experiments!


ATLAS & CMS Alignment



ATLAS & CMS Alignment

atlas schedule
ATLAS schedule

ATLAS & CMS Alignment

atlas id r view





ATLAS ID r view

ATLAS & CMS Alignment

robust alignment concept
Robust Alignment: Concept

Sum over neighbours, take correlations into account

Sum over all modules in a ring

Correct for change in radius

ATLAS & CMS Alignment

fsi track alignment
FSI + Track Alignment
  • How to include time dependency?
    • FSI provides low spatial frequency module corrections at time ti , t0<ti<t1
    • Track recorded at time ti is reconstructed using FSI module correction at time ti .
    • Global (or robust) Chi sq uses FSI corrected tracks to construct chi sq and minimises to solve for high spatial frequency modes, averaged over t0<ti<t1, low frequency modes frozen.
    • Subsequent reconstruction of track at time tj uses average alignment from global (or robust) chi sq + time dependent FSI module correction, tj, t0<tj<t1

ATLAS & CMS Alignment

Global Chi2 can add extra terms to the weight matrix and the big vector of the final system of equations to incorporate external FSI constraint