Multiplicity analysis and dN/d  reconstruction with the silicon pixel detector Terzo Convegno Nazionale sulla Fisica di ALICE Frascati (Italy) – November.

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Presentation transcript:

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)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Introduction  Acceptance coverage: SPD layers: -2.0 <  < 2.0 (inner) -1.5 <  < 1.5 (outer)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  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  

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, dN/d distributions (uncorrected) dN/d  distributions (uncorrected) asymmetry due to the detector efficiency losses in PDC06 Inner layer clusters Tracklets

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Corrections: SPD acceptance (I)  MC data samples:  Pb-Pb (HijingParam) 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  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:  Corrections: SPD acceptance (II)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Results:  convoluted acceptance & efficiency: Tracklets Inner layer Outer layer Corrections: SPD acceptance (III)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Correction applied: Corrections: acceptance & efficiency (I)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Corrections: acceptance & efficiency (II)  Correction applied:

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Clusters (inner layer): Corrections: background from secondaries (II)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Clusters (inner layer): correction (to be multiplied by) Corrections: background from secondaries (III)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  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)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Tracklets: correction (to be multiplied by) Corrections: background from secondaries (V)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  All corrections applied: inner layer clusters Final dN/d  distributions

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  All corrections applied: tracklets Final dN/d  distributions

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Multiplicity distributions (uncorrected)

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Multiplicity distributions  Background correction: 16% 7% Background fractions for each event

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Multiplicity distributions  All corrections applied:

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, MB2 =(GFO.and.V0OR).and.notBG Effect of trigger selection: first look (I)  Trigger correction:

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Effect of trigger selection: first look (II)  Generated dN/d  : MB2 =(GFO.and.V0OR).and.notBG All events No trigger No vertex

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, 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

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Backup slides

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12,  Couples of clusters associated with the same track Tracklet algorithm efficiency in p-p

Maria Nicassio Convegno Nazionale sulla Fisica di ALICE Frascati - November 12, Using the default cuts the algorithm efficiency is 99% Tracklet algorithm efficiency in p-p  Couples of clusters associated with the same track