Cosmics in ITS: tracking & alignment

IV Convegno Nazionale Fisica ALICE, Palau, 28.09.2008 Andrea Dainese 1

Cosmics in ITS: Cosmics in ITS: tracking & alignmenttracking & alignment

A.DaineseA.Dainese(INFN Legnaro)(INFN Legnaro)

ITS alignment group: LNL, PD, TS, CT, TO, Nikhef ITS alignment group: LNL, PD, TS, CT, TO, Nikhef


Layout

ITS alignment strategy

Cosmics reconstruction in ITS

Summer cosmics sample for alignment

First alignment results:

Millepede

Iterative residuals minimization

Alignment monitoring

First attempts of TPC-ITS matching

S.Moretto


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

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

residual mis. (shifts)

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

yloc

zloc

xloc

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


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 (pp) 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)

2) global ITS alignment relative to TPC (already internally aligned)

3) finally, inclusion of SDD, which need longer calibration (interplay between alignment and calibration)

Two independent track-based alignment methods in preparation:

global: Millepede (ported to ALICE for muon arm alignment)

local: iterative method based on residuals minimization


Cosmics!1st muon in SPD: Feb 17, 2008


Tracking cosmics in ITS

Cosmics tracking in ITS:adapted stand-alone ITS tracking (Torino)

enlarged search windows to account for large misalignments

start from “fake” vertex built from the two tracklets in inner two layers

ESD filewith track

space-points

ESD filewith track

space-points

Tree withSelected

Space points

Alignment procedures

Reconstruction Reconstruction

- select tracks (pt,, , #points)- can merge 2 cosmics tracks


AND

Cosmics with SPD trigger

Pixel FastOR trigger since May 25: first side C, then also side A

Trigger configuration:rate: 0.05 Hz (June) 0.18 Hz (Aug)

purity (reconstructed

with 3-4 cls/triggered): about 30%

about 85% of SPD

taking data in August

Statistics collected (till Sept 3rd): about 55k good eventsevents with 4-cls in SPD: 30k

events with 3-cls in SPD: 25k


ITS points


Cosmics statistics (SPD)220/240 (92%) modules with at least one hit200/240 (83%) modules with at least 50 hits


Cosmics statistics (SDD)Low statistics on inner layer (switched on later than outer)Limited statistics on the sides (outer layer: about 50% of modules have sufficient statistics to try alignment)


Cosmics statistics (SSD)Limited statistics on the side and edges in z

aligned in Millepede down to the ladder level: about 55/72 ladders have sufficient statiscs


SPDMillepede alignment quite advancedMost of the detectors that are currenltly switched on have some alignmentAlignment of side detectors may be less realiable

need quick checks with first pp data!

SDDCalibration of time offset is in progress (Torino)

Use Alignment Monitoring tool for validation (C.Bombonati)

Almost ready to be includedSurvey (modules on ladders) is ready to be used (M.Poghosyan)

SSDIncluded in Millepede since mid-JulyAlignment exercises usefull to spot / understand possible problems in geometry / hardware Survey (modules on ladders) ready to be used

S.Moretto

S.Moretto


Checking the quality of realignment

Main variable: track-to-track x at y=0

Acceptance overlaps “extra” clusters

Alignment monitoring tool

x

y


Millepede SPD realignment:x at y=0

realigned

not realignedSim, ideal geom:

43 m

DATA:

56 m

spatial=15 m spatial=11 m (Sim)

Expectedspread


Millepede SPD realignment:“extra” clusters

realigned

not realignedSim, ideal geom:

15 m

DATA:

22 m

spatial=16 m spatial=11 m (Sim)

Expectedspread


Alignment Monitoring: SPD

Track fit + residuals analysisCheck and monitor in time the quality of realignment

(try to “guess” high-level or correlated misalignments)

Millepede Ideal sim.

x residual [cm] x residual

C.Bombonati, A.Rossi

=70m =44mMille/Sim ~ 70/44 ~ 22/15

extraclusters


ITS alignment with tracks: iterative local method

Alignment params from minimization of 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

difficult with SPD alone: only 4 points (modules) per track

about 50% worse than Millepede;difficult to account for correlations

A.Rossi


SDD: time0 calibration and alignment

Residuals: fit su SPD+SSD

residuals su SDD (up, down)

Not indep. of misalignment

-130m -10m

C.Garcia, C.Bombonati

Complementary procedure: estimate time0 from minimum time (F.Prino)


TPC-ITS matching with large

misalignment/miscalibrationMisalignments (internal & TPC vs ITS) and miscalibration

(drift velocity, time0, ExB) reduce matching efficiency

A set of knobs to enlarge track/cluster errors should allow

to recover the efficiency

TPC: add systematic errors (drift velocity, time0, ExB) to the track

covariance matrix before prolongation to ITS

ITS: add misalignment errors to cluster errors (~ 1 mm)

Matching efficiency (prel.): TPC+ITS (4cls) / ITSsa

(4cls)

B=0: >90%

B=0.5T (enlarged errors): ~85%


B=0.5 T cosmics in ITS+TPC

pT = 1 GeV

pT = 0.2 GeV

pT = 2 GeV

noise SDDora risolto


Check of ITS alignment

with ITS+TPC tracks, B=0.5Use Millepede realignment SPD+SSD

Track-to-track distance x pull = x / √top

2+bottom

2

ITS+TPC

SPD+SSD+TPC

mean 6 m= 54 m

3or4 + 3or4 ITS points


SummaryLarge sample of cosmics collected during Summer

SPD FastOR trigger gave a big boost

All alignment machinery (reconstruction, realignment, monitoring) working from the very beginning

Good results from Millepede

Most of SPD realigned to 10 mneed cross-checks with pp, especially on the side

Started to include SSD (limited statistics for cosmics)

SDD will come soon

Next step: ITS-TPC alignmentneed to understand TPC calibration first...


EXTRA SLIDES


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+


Millepede: cross-checks (3)

Use -acceptance overlaps in SPD (“extra” clusters)

Check on simulation with ideal geometry:

(xy) = 15 m (z) = 165 mouter SPD layer:

“extra” clusters not (yet) used for realignment cross-check


Millepede: cross-checks (3)

Use -acceptance overlaps in SPD (“extra” clusters)

Check on simulation with ideal geometry:

(xy) = 22 m (z) = 163 m

high-stats sectors

selected

outer SPD layer:

raw

realigned

Cosmics in ITS: tracking & alignment

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