Primary vertex with TPConly tracks Motivation TPC standalone

Primary vertex with TPC-only tracks Motivation: TPC stand-alone analyses (multiplicity, spectra) Andrea Dainese INFN Legnaro ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 1

on subsample 1 st pass Barrel Tracking & Vertex Recons. ITS local reconstruction (➔ Rec. Points) Vertex (x, y, z) from SPD tracklets Barrel Tracking Vertex with tracks (twice: ITS+TPC, TPC only; both stored in ESD) full statistics 2 nd pass Compute diamond transverse profile, as mean and RMS of vertices in high-multiplicity events of each “LHC fill” (twice: ITS+TPC, TPC only) Repeat zvtx with SPD starting from mean (x, y) important, to have zvtx for all events (even with one tracklet), w/o bias Barrel Tracking Vertex with tracks, using info on diamond profile final (x, y) resolution better than diamond RMS for ALL events (twice: ITS+TPC, TPC only; both stored in ESD) ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 2

Vertex reconstruction with tracks Ali. Vertexer. Tracks Three main “tasks” implemented: TRACKS SELECTION Ø try reject secondary tracks VERTEX FINDING Ø give first estimate of vtx position VERTEX FITTING: Ø give optimal estimate of the position of the vertex Ø give vertex covariance matrix Ø give a c 2 (vertex quality) ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 3

Primary vertex reco with tracks Ali. Vertexer. Tracks: : Find. Primary. Vertex() Primary vertex reconstruction: iterative procedure Select tracks Ø track points to fiducual cylinder (R<3 cm, |z|<30 cm) Ø for ITS+TPC: k. ITSrefit and >4 ITS clusters Ø for TPC: k. TPCin, >50 cls and |tgl|<1 0 th iteration: Ø VERTEX FINDING, using track pairs vtx 0 1 st iteration: Ø TRACKS SELECTION: |d 03 D(vtx 0)| < 0. 5 cm for ITS+TPC < 2. 5 cm for TPC Ø VERTEX FINDING Ø VERTEX FITTING vtx 1 2 nd iteration: Ø TRACKS SELECTION: |d 0 rf(vtx 1)| < 3 sd 0 Ø VERTEX FINDING Ø VERTEX FITTING vtx 2 (final estimate) ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 4

Impact parameter distr. of TPC tracks z rf reasonable pulls ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 5

Diamond constraint Why diamond constraint? vertex also for events with 1 “primary” track better rejection of secondaries (x, y) resolution always better than diamond size Exercise on CAF (as it could be done on the data) use 10 k triggered events, pp 900 Ge. V select vertices with > 10 tracks weighted average of (x, y, z) diamond: Ø centre: weighted average (tried also with plain average: compatible results) Ø sigma: error of weighted average (20 -30 mm) diamond rms from machine (200 mm @ 900 Ge. V) use this diamond as constraint and re-evaluate vertices (2 nd reconstruction pass) 6

TPC Vertex efficiency Efficiency: events with vertex / triggered (MB 1=SPD||V 0 A||V 0 C) Different normalization: events with vertex / events triggered and with >0 TPC tracks pointing to the beam pipe 7

TPC Vertex efficiency PHOJET 900 0 T PHOJET 900 0. 5 T 8

Resolutions and pulls (PHOJET 900 0 T) closed markers: RMS; open markers: s fit no constraint First Physics test production (TPC misaligned, miscalibrated) no constraint with constraint Ideal simulation and reconstruction with constraint 9

Code Ali. Vertexer. Tracks can take an array (TObj. Array) of Ali. External. Track. Param tracks Separate “Mean. Vertex” objects in OCDB for ITS+TPC and TPC-only Selection criteria for Ali. Vertexer. Tracks kept in new class Ali. GRPReco. Param (from rec. C or OCDB) separate criteria (incl. constraint flag) for ITS and TPC “mode” performance optimisation without touching compiled code In Ali. Reconstruction: Ali. Vertexer. Tracks t. Vertexer; // TPC + ITS primary vertex t. Vertexer. Set. Vtx. Start(f. Diamond. Profile); // from OCDB t. Vertexer. Set. ITSMode(grp. Reco. Param->Get. ITSCuts()); . . . find vertex ESD // TPC-only primary vertex t. Vertexer. Set. Vtx. Start(f. Diamond. Profile. TPC); // from the OCDB t. Vertexer. Set. TPCMode(grp. Reco. Param->Get. TPCCuts()); . . . find vertex ESD ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 10

Next The extraction of the mean vertex and storage in the OCDB is run manually on CAF OK for first data at 900 Ge. V check stability of diamond position vs time, run#, . . . Later the procedure will have to become automatic and run on ESDs accessed on grid how to identify the run/event/time at which the diamond moves? 11

Comparison with MC vertex: shift First Physics test production (TPC misaligned, miscalibrated) Ideal simulation and reconstruction 12

Tracks Selection Idea: use “primary” tracks for vertex reconstruction Only tracks with 5 or 6 points in ITS Select primary tracks on the basis of their d 0 Cut |d 0| < n sd 0(pt) = svtx strack(pt) y from track’s covariance matrix track vertex x need an estimate of the vertex and its cov. matrix ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 13

Vertex Fitter “Fast Vertex Fitting”, CMS Note 1997/051 Tracks are propagated to the point given by the vtx finder Each track gives an independent measurement of the vertex position: a c 2 is written as the sum of the single track c 2 s w. r. t. a generic vertex position rvtx: where ri is the (x, y, z) position of the ith track and Vi = Wi-1 is the cov matrix of ri, extracted from the track’s cov matrix The solution that minimizes this c 2 is analytic: vertex ALICE Offline Week, CERN, 22. 10. 08 vertex covariance matrix Andrea Dainese 14

Easy to add “beam constraint” Same procedure as before + constraint: vertex covariance matrix where: ALICE Offline Week, CERN, 22. 10. 08 Andrea Dainese 15