Download presentation
Presentation is loading. Please wait.
Published byMarie Richard Modified over 9 years ago
1
Multiplicity analysis and dN/d reconstruction with the silicon pixel detector Terzo Convegno Nazionale sulla Fisica di ALICE Frascati (Italy) – November 12-14, 2007 Maria Nicassio (Univ. and INFN Bari) in collaboration with D. Elia, B. Ghidini (Univ. and INFN Bari) T. Virgili (Univ. Salerno)
2
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 2 Contents Introduction: physics motivation tracklet reconstruction algorithm Status of the analysis: study of the corrections: geometrical acceptance detector efficiency background from secondaries vertex reconstruction efficiency minimum bias trigger acceptance Summary and outlook
3
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 3 Introduction Why multiplicity: first measurement in p-p collisions for ALICE global observable characterizing the event comparison with results obtained at lower energies Why multiplicity with pixels: available in a short time advantages over reconstructed tracks (ITS+TPC) larger acceptance coverage only alignment of the two pixel layers required
4
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 4 Introduction Acceptance coverage: SPD layers: -2.0 < < 2.0 (inner) -1.5 < < 1.5 (outer)
5
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 5 Multiplicity reconstruction: (a) counting clusters on the inner layer (| | < 2.0) no detector alignment required reliable at high multiplicity (b) counting tracklets (| | < 1.5) alignment, vertex needed more reliable (e.g. good noise rejection) Pseudorapidity reconstruction: vertex needed for both methods the angle of the cluster on the inner layer is used Introduction Fiducial window
6
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 6 dN/d distributions (uncorrected) dN/d distributions (uncorrected) asymmetry due to the detector efficiency losses in PDC06 Inner layer clusters Tracklets
7
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 7 Corrections: SPD acceptance (I) MC data samples: Pb-Pb (HijingParam) collisions @ 5.5 TeV: 20,000 tracks/evt, within [-4,4] event vertex-Z within [-20,20] cm fully efficient SPD 2,500 evts pure geom acceptance standard PDC06 SPD dead chip map 2,500 evts convoluted acc+eff Correction matrix: binning and range: within [-3,3] nEtabins = 120 d = 0.05 vtx-Z within [-20,20] cmnVtxzbinx = 40 dVtx-Z = 1 cm
8
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 8 Calculation method: detectable_tracks ( fDenAcc ): primary charged no decay, no secondary interactions up to the sensitive layer detected_tracks ( fNumAcc ): detectable tracks with associated (label) cluster on the sensitive layer if there are 2 clusters on adjacent modules: track is counted twice this takes into account the overlapping regions ( 2%) compute acceptance and error in each bin ( fAcc,fErrAcc ) statistics in each bin: detectable tracks: 10 4 resulting error on the acceptance: 10 -3 Corrections: SPD acceptance (II)
9
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 9 Results: convoluted acceptance & efficiency: Tracklets Inner layer Outer layer Corrections: SPD acceptance (III)
10
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 10 Correction applied: Corrections: acceptance & efficiency (I)
11
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 11 Corrections: acceptance & efficiency (II) Correction applied:
12
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 12 Corrections: background from secondaries (I) Studied using the SPD cluster labels Definition of background: for clusters on the inner layer: clusters having secondary track labels only for tracklets: at least one of the two clusters in the tracklet having secondary track labels only
13
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 13 Clusters (inner layer): Corrections: background from secondaries (II)
14
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 14 Clusters (inner layer): correction (to be multiplied by) Corrections: background from secondaries (III)
15
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 15 Tracklets: Tracklets from primaries Tracklets from secondaries Tr(P+P) Tr(P+P’) Tr(P+P)+Tr(P+P’) Tr(S+S) + Tr(P+S) Tr(S+S) Tr(P+S) to be subtracted P, P’ = cluster with a label of a primary track S = cluster with all labels of secondary tracks (total bkg fraction: 7.5%) Corrections: background from secondaries (IV)
16
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 16 Tracklets: correction (to be multiplied by) Corrections: background from secondaries (V)
17
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 17 Corrections: vertex reconstruction (I) Generated dN ch /d N.B. The correction is integrated, but it should be a function of multiplicity and vertex position
18
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 18 Correction (to be multiplied by) Corrections: vertex reconstruction (III) The correction depends both on and on multiplicity at low multiplicity To be checked as a function of Z-vtx
19
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 19 All corrections applied: inner layer clusters Final dN/d distributions
20
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 20 All corrections applied: tracklets Final dN/d distributions
21
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 21 Multiplicity distributions (uncorrected)
22
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 22 Multiplicity distributions Background correction: 16% 7% Background fractions for each event
23
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 23 Multiplicity distributions All corrections applied:
24
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 24 MB2 =(GFO.and.V0OR).and.notBG Effect of trigger selection: first look (I) Trigger correction:
25
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 25 Effect of trigger selection: first look (II) Generated dN/d : MB2 =(GFO.and.V0OR).and.notBG All events No trigger No vertex
26
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 26 Summary and outlook Multiplicity and pseudorapidity density in p-p: first measurement in ALICE reconstruction with the Silicon Pixel Detector only Status of the analysis: raw reconstructed distributions with PDC06 data study of the main corrections: acceptance, efficiency, background from secondaries, vertex, trigger What next: check correction dependence on multiplicity, Z-vtx estimate of the systematics tests with PDC07 data
27
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 27 Backup slides
28
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 28 Couples of clusters associated with the same track Tracklet algorithm efficiency in p-p
29
Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 2007 29 Using the default cuts the algorithm efficiency is 99% Tracklet algorithm efficiency in p-p Couples of clusters associated with the same track
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.