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IV Convegno Nazionale Fisica ALICE, Palau, 28.09.2008 Andrea Dainese 1 Cosmics in ITS: tracking & alignment A.Dainese (INFN Legnaro) ITS alignment group:

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Presentation on theme: "IV Convegno Nazionale Fisica ALICE, Palau, 28.09.2008 Andrea Dainese 1 Cosmics in ITS: tracking & alignment A.Dainese (INFN Legnaro) ITS alignment group:"— Presentation transcript:

1 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 1 Cosmics in ITS: tracking & alignment A.Dainese (INFN Legnaro) ITS alignment group: LNL, PD, TS, CT, TO, Nikhef

2 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 2 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

3 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 3 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) SPD SSD SDD ITS total: 2198 alignable sensitive volumes  d.o.f.

4 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 4 ITS detector resolutions & target alignment precisions Residual: expected misalignment left after applying the realignment procedure(s). Target ~0.7  resol.  ~20% degradation of the resolution SPD (r = 4 & 7 cm) SDD (r = 14 & 24 cm) SSD (r = 39 & 44 cm) nom. resolutions x loc  (y loc )  z loc [  m 3 ] 12  (0)   (0)  2020  (0)  830 residual mis. (shifts) x loc  y loc  z loc [  m 3 ] 10  10  2020  20  2015  15  100 y loc z loc x loc detector local c.s.: x loc ~r  glob, y loc ~r glob, z loc = z glob

5 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 5 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  (12-20  m), worse in z (  m) 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

6 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 6 Cosmics! 1st muon in SPD: Feb 17, 2008

7 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 7 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 file with track space-points Tree with Selected Space points Alignment procedures Reconstruction - select tracks (p t, , , #points) - can merge 2 cosmics tracks

8 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 8 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 events events with 4-cls in SPD: 30k events with 3-cls in SPD: 25k

9 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 9 ITS points

10 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 10 Cosmics statistics (SPD) 220/240 (92%) modules with at least one hit 200/240 (83%) modules with at least 50 hits

11 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 11 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)

12 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 12 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

13 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 13 SPD Millepede alignment quite advanced Most of the detectors that are currenltly switched on have some alignment Alignment of side detectors may be less realiable  need quick checks with first pp data! SDD Calibration of time offset is in progress (Torino) Use Alignment Monitoring tool for validation (C.Bombonati) Almost ready to be included Survey (modules on ladders) is ready to be used (M.Poghosyan) SSD Included in Millepede since mid-July Alignment exercises usefull to spot / understand possible problems in geometry / hardware Survey (modules on ladders) ready to be used  S.Moretto

14 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 14 Checking the quality of realignment Main variable: track-to-track  x at y=0 Acceptance overlaps  “extra” clusters Alignment monitoring tool x y

15 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 15 Millepede SPD realignment:  x at y=0 realigned not realigned Sim, ideal geom: 43  m DATA: 56  m   spatial =15  m   spatial =11  m (Sim) Expected spread

16 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 16 Millepede SPD realignment: “extra” clusters realigned not realigned Sim, ideal geom: 15  m DATA: 22  m   spatial =16  m   spatial =11  m (Sim) Expected spread

17 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 17 Alignment Monitoring: SPD Track fit + residuals analysis Check and monitor in time the quality of realignment (try to “guess” high-level or correlated misalignments) MillepedeIdeal sim. x residual [cm] x residual C.Bombonati, A.Rossi  =70  m  =44  m Mille/Sim ~ 70/44 ~ 22/15 extra clusters

18 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 18 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

19 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 19 SDD: time0 calibration and alignment Residuals: fit su SPD+SSD residuals su SDD (up, down) Not indep. of misalignment -130  m-10  m C.Garcia, C.Bombonati Complementary procedure: estimate time0 from minimum time (F.Prino)

20 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 20 TPC-ITS matching with large misalignment/miscalibration Misalignments (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%

21 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 21 B=0.5 T cosmics in ITS+TPC p T = 1 GeV p T = 0.2 GeV p T = 2 GeV noise SDD ora risolto

22 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 22 Check of ITS alignment with ITS+TPC tracks, B=0.5 Use 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

23 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 23 Summary Large 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  m need cross-checks with pp, especially on the side Started to include SSD (limited statistics for cosmics) SDD will come soon Next step: ITS-TPC alignment need to understand TPC calibration first...

24 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 24 EXTRA SLIDES

25 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 25 Primary Vertex B e X d0d0 rec. track Impact of ITS misalignment on tracking performance Effect of misalignment on d 0 (and p t ) resolutions studied by reconstructing misaligned events with ideal geometry Estimated effect on D 0  K  significance A.D, A.Rossi null residual full full+

26 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 26 Millepede: cross-checks (3) Use  -acceptance overlaps in SPD (“extra” clusters) Check on simulation with ideal geometry:  (  xy) = 15  m  (  z) = 165  m outer SPD layer: “extra” clusters not (yet) used for realignment  cross-check

27 IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 27 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


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