terzo convegno sulla fisica di alice - lnf, 14.11.07 andrea dainese 1 preparation for its alignment...

Terzo Convegno sulla Fisica di ALICE - LNF, 14.11.07 Andrea Dainese 1

Preparation for ITS alignmentPreparation for ITS alignment

A. DaineseA. Dainese(INFN – LNL)(INFN – LNL)

for the ITS alignment group (CERN, LNL, NIKHEF, PD, TS)for the ITS alignment group (CERN, LNL, NIKHEF, PD, TS)

What? What? ITS detectors, target alignment precisionITS detectors, target alignment precision Why? Why? Impact of misalignmentsImpact of misalignments How? How? Strategy and methodsStrategy and methods How well? How well? First results from simulationFirst results from simulation


Inner Tracking System (ITS)

Silicon Pixel Detector (SPD):• ~10M channels• 240 sensitive vol. (60 ladders)

Silicon Drift Detector (SDD):• ~133k channels• 260 sensitive vol. (36 ladders)

Silicon Strip Detector (SSD):• ~2.6M channels• 1698 sensitive vol. (72 ladders)

SPDSSD

SDD

ITS total:2198 alignable sensitive volumes 13188 d.o.f.


ITS detector resolutions & target alignment precisions

Full: initial misalignments as expected from the mechanical imprecision after installation, actually set to 20-45 m at the sensor level, probably higher at the ladder or layer level (~100 m), more later...Residual: expected misalignment left after applying the realignment procedure(s). Target ~0.7resol. ~20% degradation of the resolution

SPD(r = 4 & 7 cm)

SDD(r = 14 & 24 cm)

SSD(r = 39 & 44 cm)

nom. resolutions

xloc (yloc) zloc [m3] 12 (0) 120 38 (0) 20 20 (0) 830

full mis. (shifts)

xlocyloczloc [m3] 20 20 20 45 45 45 30 30 100

residual mis. (shifts)

xlocyloczloc [m3] 10 10 20 20 20 20 15 15 100

rotations (mrad)

around xloc,yloc,zloc 0.3 0.3 0.3

yloc

zloc

xloc

detector local c.s.: xloc~rglob, yloc~rglob, zloc = zglob


PrimaryVertex B

e

Xd0

rec. track

Impact of ITS misalignmenton tracking performance

Effect of misalignment on d0 (and pt) resolutions studied by reconstructing misaligned events with ideal geometry

Estimated effect on D0K significance

A.D, A.Rossi

nullresidualfullfull+


Introduction of “realistic” misalignment

Why “realistic”?1. misalignment should follow hierarchy of hardware structure; each level

should be misaligned (and then realigned)

2. magnitude of initial misalignments should be realistic (input from hardware experts)

3. misalignments at the same hierarchical level should be correlated

E.g., for SPD: barrel / half-barrel / sector / half-stave / ladder# sensitive volumes: 240 / 120 / 24 / 2 / 1

magnitude of misal. (m): <1000 / ~100 / ~100 / 10-50 / 5

(up to now only the ladder was misaligned)

Transition to realistic misalignment is in progress (requires changes to the ITS geometry)

Will provide:better playground for preparation of realignment procedures

better estimate of effects of residual misalignments on performance


ITS alignment with tracks:general strategy

Data sets: cosmics + first pp collisions (and beam gas)use cocktail of tracks from cosmics and pp to cover full detector surface and to maximize correlations among volumes

Start with B off, then switch on B possibility to select high-momentum (no multiple scattering) tracks for alignment

General strategy:1) start with layers easier to calibrate: SPD and SSD

good resol. in r (12-20m), worse in z (120-830m) ITS z resol. provided by SDD anode coord. (20m) easily

calibrated can be included from the beginning in alignment chain

2) global ITS alignment relative to TPC (already internally aligned)3) finally, inclusion of SDD (drift coord: r), which probably need longer

calibration (interplay between alignment and calibration)Two independent track-based alignment methods in preparation:

global: Millepede 1 (ported to ALICE for muon arm alignment)local: iterative method based on residuals minimization


Preparation for cosmics data (1) Cosmics Run in February 2008

Expected muon rate through ITS inner layer (~200cm2, ~40m underground): ~0.02 Hz ( ~104 /week)

Trigger with SPD layers (tracks with 10-12 points):

Trigger with ACORDE (“peripheral” tracks with 4-8 points in SSD-SDD)

FastOR (FO) of the 20 chips on 2 half-staves

For each half-barrel (A side, C side): 20 FOs outer layer, 10 FOs inner layer Any logic combination of these 30 FOs

SPD FastOR

Option being considered for cosmics:

2Layers coinc. (≥2FOs inn layer & ≥2FOs out layer)

purity (fraction with 1 with 4 SPD hits): ~97%,

inefficiency (fraction of lost with 4 SPD hits): ~19%

A side

C side

D.Elia


Preparation for cosmics data (2)Cosmics at ALICE: p > 10 GeV/c, <p>~20 GeV/c (Hebbeker, Timmermans, 2001)

Cosmics tracking in ITS:modified stand-alone ITS tracking (cluster-grouping algorithm from Torino)

98% efficiency (12 points, 6inward+6outward) for muons that leave 12 hits, with B=0 and B=0.5T

high eff (~80-90%) also for muons crossing only outer layers

robustness tested with “extreme” misalignment scenarios

tracks prolongation from TPC to ITS being optimized for cosmics

Preparing first d0 resolution meas. by cosmics two-track matching

d0=12m d0=21m

no misal.

fullmisal.

A.D.,A.Jacholkowski


Cosmics in the ITS50k ’s through inner ITS layer (~5 weeks of cosmics data)

Track multiplicity per module:

SPD inner

A.Rossi

6 pts tracks

12 ptstracks

Volume correlations. Number of modules correlated to a given module:

SPD inner SDD inner SSD inner103

102

10

1

103

102

10

1

103

102

10

1

800 800

400 400


Track-based alignment in the barrel (ITS, TPC, TRD, ...)

- Framework Overview -

ESD filewith track

space points

ESD filewith track

space points

ESD filewith track

space points

ESD filewith track

space points

Tree withselected

space points

Alignment procedures

Local file

Local

Iterative residuals minimizationMillepede...

Distributed/CAF

Reconstruction Reconstruction Reconstruction Reconstruction

C.Cheskov


ITS alignment with tracks:the global approach of Millepede

M.Lunardon, S.Moretto

Determine alignment parameters of “all” modules in one go, by minimizing the global 2 of track-to-points residuals for a large set of tracks (cosmics + pp)

Linear problem: the points residuals can be expressed as a linear function of the (global, di) alignment params and (local δi) tracks’ params

At the moment being tested with cosmics tracks and B=0

Strategy for tests:1. validate algorithm with “fast simulation” (no detector response)

2. introduce full detector response


xLOC

yLOC

zLOC

• 5 weeks of cosmics (50k in SPD1), B=0• Tracks with 12 pts• 375 modules (out of 2198)

SPD SDD SSD

inputresultdifference

Millepede with fast simulation

yloc

zloc

xloc


As a function of the number of minimum # of points per track

SPD

x y z

Millepede with fast simulationRMS of (result-input)

• 5 weeks of cosmics (50k in SPD1) , B=0• Also tracks with <12 pts

SDD similar to SPD

better with “peripheral tracks”

5m!


As a function of the number of minimum # of points per track

SSD

x y z

Millepede with fast simulationRMS of (result-input)

• 5 weeks of cosmics (50k in SPD1), B=0• Also tracks with <12 pts

much better with “peripheral tracks”


Millepede: fast vs. full simulation

Deterioration of results with full detector simulation

This triggered investigations on the different steps of the simulation, with misalignment found problems with overlaps that caused shift of ITS rec. points will be solved in new ITS geometry

For the moment, continue alignment studies without misalignments


PARAM SPD SDD SSD

mean RMS mean RMS mean RMS

x (m) -1.4 4.9 0.7 4.6 1.0 8.2

y (m) 0.9 7.6 19.1 16.3 5.3 66.0

z (m) 1.0 5.7 -0.3 4.6 -0.4 63.7

(mdeg) -0.9 15.6 -1.5 20.5 6.7 191

(mdeg) -0.7 9.2 0.0 5.6 -1.9 25.7

(mdeg) 14.3 43.1 -1.6 25.7 3.7 152.5

• about 5 weeks of cosmics, B=0• 663 modules ( 135 SPD + 104 SDD + 424 SSD )

Millepede: full simul., no misal.



Millepede: full simul., no misal.SPD only, SPD+SSD

• about 5 weeks of cosmics, B=0• 612 modules ( 192 SPD + 420 SSD )

PARAM SPD RMS SSD RMSSPD only SPD+SSD SPD+SSD

x (m) 8 6 14

y (m) 19 12 71

z (m) 13 11 60

(mdeg) 36 28 199

(mdeg) 10 7 20

(mdeg) 50 48 161

SPD: worse on the sides need pp tracks

z

top

bottom



ITS alignment with tracks: iterative local method

Iterations loop(user-defined)

Loop over volumes(user-defined)

Update alignmentobjects

Align volume(s) Aw.r.t. volume(s) B

OCDB

Fit points in volume(s) B (several fitters available for

straight line and helix tracks) and extrapolate

tracks to volume(s) A

Minimize (several minimizers

available), w.r.t. alignmentparams of volume(s) A,

residuals between pointsand extrapolations

in volume(s) A

C.CheskovA.Rossi

Determines alignment params by minimizing track-to-points residuals

Local: works on a module-by-module basis

Iterations are used to take into account correlations between the alignment params of different modules


PARAM SPD RMS SDD RMS SSD RMS

Iter Millep Iter Millep Iter Millep

x (m) 2 5 3 5 5 8

y (m) 7 8 20 16 64 66

z (m) 8 6 3 5 60 64

(mdeg) 17 16 40 21 -- 191

(mdeg) 6 9 8 6 16 26

(mdeg) 58 43 43 26 -- 153

• about 5 weeks of cosmics, B=0• no iterations (not necessary without misalignment)

Iterative local method: full simul., no misal.

A.Rossi


Iterative local method:full simul. with misal., iterations

SPD inner: mean, RMS

global

glob

al z

(cm

)

x (m)

A.Rossi

iterationsconvergence

worse on the sides need pp tracks


ITS-TPC relative alignment

Relative alignment of ITS and TPC (3 shifts + 3 angles) with straight tracks (including cosmics)Alignment requirements: given by TPC resolutions:

shifts: ~100 mangles: ~0.1 mrad

Method (under development):Assume that TPC and ITS are already

internally aligned and calibratedUse independently fitted tracks

in the ITS and the TPCAlignment params are estimated

by a Kalman filter algorithmProof-of-principle test with

“toy” tracks

M.Krzewicki


Summary

The ITS alignment challenge: determine 13,000 parameters with a precision of ~10 m

Track-based alignment using cosmics and pp collisionspreparation for cosmics reconstruction in ITS

Two independent algorithms under developmentMillepede (global)

local iterative method

Promising results even with cosmics only, should be much better with cosmics + pp tracks

ITS alignment relative to TPC also under study


EXTRA SLIDES


1. A muon direction is generated

2. Intersection points with misaligned detectors are evaluated in local coordinate systems• large misal. order of 100 m

3. Points smeared with given resolutions

4. Use tracks with 4-12 points

Advantages w.r.t. standard sim:

• clean situation, without simulation/reconstruction effects

• faster

Fast Simulation

terzo convegno sulla fisica di alice - lnf, 14.11.07 andrea dainese 1 preparation for its alignment...

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