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Outline  motivations  methods: ITS: TPC+ITS(-1 layer) tracks SPD: SPD standalone  tracklets  strategy with data  conclusions Studi di Efficienza dell’ITS.

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Presentation on theme: "Outline  motivations  methods: ITS: TPC+ITS(-1 layer) tracks SPD: SPD standalone  tracklets  strategy with data  conclusions Studi di Efficienza dell’ITS."— Presentation transcript:

1 Outline  motivations  methods: ITS: TPC+ITS(-1 layer) tracks SPD: SPD standalone  tracklets  strategy with data  conclusions Studi di Efficienza dell’ITS Giuseppe E Bruno Università di Bari and INFN - Italy intended for first paper

2 30/09/2008III Convegno Fisica di Alice G.E. Bruno2 Plane efficiencies: what’s for ?  from data to a paper data taking  raw data reconstruction  ESD  standard AOD analysis:  standard AOD  user AOD  selection of candidates  computation of corrections for acceptance and reconstruction inefficiencies  estimate of the systematics errors (here corrections always play a role) writing of the paper

3 30/09/2008III Convegno Fisica di Alice G.E. Bruno3 Efficiency of a given ITS layer: how ?  build tracks without using that layer  search for clusters compatible with the track predictions on that layer Eff=N succ /N tracks

4 30/09/2008III Convegno Fisica di Alice G.E. Bruno4 Implemented ITS segmentation  pixel: chip by chip n. of tracks layer 1: 400 chips 160K layer 2: 800 chips 323K  drift: chip by chip layer 3: 672 chips271K layer 4: 1408 chips567K  strip: module by module layer 5: 748 modules302K layer 6: 950 modules383K Eff= 99% The code is flexible enough to easily reduce/enlarge segmentation

5 30/09/2008III Convegno Fisica di Alice G.E. Bruno5 A general scheme Any tracker: AliITStrackerMI ITS standalone Trackleter Macro: ITS refitted tracks + clusters Plane Efficiency AliITSPlaneEff AliITSPlaneEffSXD Data Base Efficiencies Root Files: histos of residuals, etc. i/o Container Class

6 30/09/2008III Convegno Fisica di Alice G.E. Bruno6 Plane efficiency measured using high quality tracks: TPC + 5/6ITS TPC ITS track zoom Not available on day 1: it can be applied after ITS and TPC alignement

7 30/09/2008III Convegno Fisica di Alice G.E. Bruno7 Tuning of AliITStrackerMI  residual misalignment scenario (after alignement): AliITSRecoParam *AliITSRecoParam::GetPlaneEffParam(Int_t i) // optimized setting for SPD0 (i==0) if (i==0 || i==1) { param->fMinPtPlaneEff = 0.200; // high pt particles param->fMaxMissingClustersPlaneEff = 1; // at most 1 layer out of 5 without cluster param->fRequireClusterInOuterLayerPlaneEff = kTRUE; // cluster on SPD1 //param->fOnlyConstraintPlaneEff = kTRUE; } if (i==2 || i==3) { param->fMinPtPlaneEff = 0.200; // high pt particles param->fMaxMissingClustersPlaneEff = 1; // at most 1 layer out of 5 without cluster param->fRequireClusterInOuterLayerPlaneEff = kTRUE; //param->fOnlyConstraintPlaneEff = kTRUE; } if (i==4) { …….  a try also for full misalignement (day one): method can be applied to SSD; bias in SPD and SDD

8 30/09/2008III Convegno Fisica di Alice G.E. Bruno8 results for 30K pp m.b. events SPD0 SPD residual misalignemet chip v4-13-release SDD1 chip

9 30/09/2008III Convegno Fisica di Alice G.E. Bruno9 SSD0 SSD1 initial misalignemet results for 20K pp m.b. events method can be applied with inital misalignemet only for SSD SPD1 (similarly SDD) module

10 30/09/2008III Convegno Fisica di Alice G.E. Bruno10 Evaluation of the SPD chip efficiencies using tracklets  Motivations: SPD chip efficiencies with tracks would not be available on day one pixel “efficiency” from map of hits is not an absolute measurements  Strategy: build tracklets using two “points”:  reconstructed primary vertex (at least Z)  cluster on one layer search - on the other layer - for a cluster compatible with the tracklet prediction Eff mes (chip)=N succ (chip)/N tried (chip) ? ? This would be true eff. if - no “secondaries” - no background

11 30/09/2008III Convegno Fisica di Alice G.E. Bruno11 Evaluation of the SPD chip efficiencies using tracklets Fiducial window   Failure Success Fiducial window 

12 30/09/2008III Convegno Fisica di Alice G.E. Bruno12  “Non-reconstructables” (largest bias) A method based on MonteCarlo is needed to correct for “non-reconstructables” (but it would rely on the efficiencies themselves) Corrections: (I) E.g. most of secondary particles About 15% (30%) of the tracklet predictions on the outer (inner) layer would not match a cluster due to non-reconstructable particles (mainly secondaries), not to chip inefficiency

13 30/09/2008III Convegno Fisica di Alice G.E. Bruno13 Correction for “non-reconstructables” (i) reconstructable trackletsnon reconstructable tracklets can only be determined from MC simulation

14 30/09/2008III Convegno Fisica di Alice G.E. Bruno14 Correction for combinatorial background (i) Missing cluster due to inefficiency Another cluster within the fiducial window from a different particles Computed using a numerical iteration

15 30/09/2008III Convegno Fisica di Alice G.E. Bruno15 Correction for combinatorial background (ii) is the probability to reconstruct a tracklets from two uncorrelated Rec-Points All the introduced quantities have to be evaluated chip by chip, e.g., It can be evaluated on the data themeself, by (e.g.) applying a rotation of 180° around the z axis to all the RecPoints on a given layer

16 30/09/2008III Convegno Fisica di Alice G.E. Bruno16 Implementation of the “trackleter” and results  The trackleter has been developed, intensively tested and tuned  It is in AliRoot since v4-13-Release: ITS/AliITSTrackleterSPD  Two MC productions (30K events each) for testing/developing the procedure 1.expected efficiencies: ~ 100% for working chips, 0% for a few dead modules/chips 2.unrealistically low chip efficiencies (67%)

17 30/09/2008III Convegno Fisica di Alice G.E. Bruno17 Results: sample 1  30K pp min-bias  Expected efficiency: overall:# dead < 0.1%  100% efficiency 1 dead half stave in the inner layer

18 30/09/2008III Convegno Fisica di Alice G.E. Bruno18 Results: sample 2  30K pp min-bias  Ad hoc created Pixel dead map 11 contiguos dead columns in each chip (32 columns/chip) block of dead columns randomly placed inside each chip  Exspected chip efficiency = 11/ /32*chip_overlapping /32 = 65.6% + ≈1.3% + 0.5% = 67.5% charge diffusion about 2%

19 30/09/2008III Convegno Fisica di Alice G.E. Bruno19 Results: sample 2 Expected ≈ 67.5%

20 30/09/2008III Convegno Fisica di Alice G.E. Bruno20 Procedure for data  special macros to be run after standard reconstruction for sub-set of data (chuncks) recplaneeff.C (x6)  ITS+TPC tracking EvaluateSPDEffWithTracklets.C (in $ALICE_ROOT/ITS)  output: root files with PlaneEff statistics, histos, etc.  2 nd task to collects outputs from several chuncks, sum up statistics and update OCDB Implemented and tested in the official PDC08 MC productions for first physics this summer

21 30/09/2008III Convegno Fisica di Alice G.E. Bruno21 Results of a mock analysis for one of such productions  “data” = Pythia (10k events)  MC=Phojet (100k events) SPD0 SPD1 chip n. Field= 0.5T Energy=900GeV

22 30/09/2008III Convegno Fisica di Alice G.E. Bruno22 Conclusions  a framework for the evaluation of the ITS efficiency has been developed (since our last meeting in Frascati)  it has been designed for being exportable to other barrel detectors (e.g. TOF,TRD)  a special method for SPD with tracklets has been implemented in view of the first paper  Tools are integrated in the standard reconstruction

23 30/09/2008III Convegno Fisica di Alice G.E. Bruno23 Backup slides Thank you Andrea

24 30/09/2008III Convegno Fisica di Alice G.E. Bruno24 Code implementation for ITS ITS Tracker AliITStrackerMI Reco Param AliITSRecoParam Plane Efficiency AliITSPlaneEff AliITSPlaneEffSXD Data Base  AliITSRecoParam: steer special setting of tracking for Plane Efficiency determination, e.g. SetLayerToSkip(i)  AliITStrackerMI: tracking without the plane under study search for the clusters on the skipped layer Root Files: histos of residuals, etc. i/o

25 30/09/2008III Convegno Fisica di Alice G.E. Bruno25 possible developments  require special constraint of the track to the primary vertex  Improve spatial precison of track at intermediate layers use innermost points to build a 2 nd track improve track parameter by combining the two halfs

26 30/09/2008III Convegno Fisica di Alice G.E. Bruno26 SDD segmentation for efficiency evaluation  layer 3: 14 ladders 1 ladder=6 detector tot. 84 detector  layer 4: 22 ladders 1 ladder=8 detector tot. 176 detector  each detector divided in 8(chips) times, eventually 2 (drift direction) zones layer 3: 672 (*2) zones layer 4: 1408(*2)zones

27 30/09/2008III Convegno Fisica di Alice G.E. Bruno27 Correction for “non-reconstructables” (ii) can only be determined from MC simulation moreover, for the chips on a given layer, depends on the efficiencies of the chips on the other layer (that used to build the tracklet prediction) In principle, one should apply an iterative procedure to compute this ratio; actually the usage of Eff mes (chip) is enough In fact, N rec (chip) and N n.rec (chip) are computed by counting the number of tracklet predictions on the given chip with or without, respectively, at least one MC TrackRef associated to the same particles which generated the RecPoints used to build the tracklet prediction (info from MC Stack), which is inside the fiducial window, as for real tracklets


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