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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

  • 2007-2008


    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

    track minimizing residuals

    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 minimizing residuals

    • 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

    double minimizing residuals




    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.. minimizing residuals

    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 minimizing residuals

    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 minimizing residuals

    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

    Nominal minimizing residuals

    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 minimizing residuals

    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 minimizing residuals


    (1 dead)

    6 PIXEL






    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

    Time recorded (22% of SCT,








    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 recorded (22% of SCT, 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

    BCam recorded (22% of SCT,




    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

    EndCap recorded (22% of SCT,


    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 recorded (22% of SCT,

    • 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

    Z-sensors recorded (22% of SCT,


    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 recorded (22% of SCT,

    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

    ATLAS TRT+SCT Endcap recorded (22% of SCT,

    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 recorded (22% of SCT, 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

    BACKUP and answering my questions.

    ATLAS & CMS Alignment

    Atlas schedule
    ATLAS schedule and answering my questions.

    ATLAS & CMS Alignment

    Atlas id r view

    107cm and answering my questions.




    ATLAS ID r view

    ATLAS & CMS Alignment

    Robust alignment concept
    Robust Alignment: Concept and answering my questions.

    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 and answering my questions.

    • 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

    The challenge of putting it all together alignment data flow martin weber
    The challenge of putting it all together: and answering my questions.Alignment data flow (Martin Weber)

    ATLAS & CMS Alignment