Primary vertex reconstruction with the SPD

Slides:



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

Multiplicity analysis and dN/d  reconstruction with the silicon pixel detector Terzo Convegno Nazionale sulla Fisica di ALICE Frascati (Italy) – November.
D. Elia, INFN BariALICE Offline Week - June Recent results from SPD beam test D. Elia, R. Santoro INFN Bari ALICE Collaboration - SPD Group.
III Convegno sulla Fisica di ALICE. Frascati 1 Vertex reconstruction and selection strategies for D s detection in Pb-Pb collisions Sergey Senyukov,
IV Convegno Nazionale Fisica ALICE, Palau, Andrea Dainese 1 Cosmics in ITS: tracking & alignment A.Dainese (INFN Legnaro) ITS alignment group:
June 6 th, 2011 N. Cartiglia 1 “Measurement of the pp inelastic cross section using pile-up events with the CMS detector” How to use pile-up.
1 PID Detectors & Emittance Resolution Chris Rogers Rutherford Appleton Laboratory MICE CM17.
PPR meeting - January 23, 2003 Andrea Dainese 1 TPC tracking parameterization: a useful tool for simulation studies with large statistics Motivation Implementation.
Vertex reconstruction in ALICE
Preliminary analysis of p-Pb data update n. 6 Lorenzo Bonechi LHCf Catania meeting – 19 December 2013.
Mitglied der Helmholtz-Gemeinschaft Calibration of the COSY-TOF STT & pp Elastic Analysis Sedigheh Jowzaee IKP Group Talk 11 July 2013.
Tracking, PID and primary vertex reconstruction in the ITS Elisabetta Crescio-INFN Torino.
UC Davis June st Rosi Reed Low Energy Test Run Results Rosi Reed University of California at Davis.
ALICE Offline Week, CERN, Andrea Dainese 1 Primary vertex with TPC-only tracks Andrea Dainese INFN Legnaro Motivation: TPC stand-alone analyses.
1 Vertex Finding in AliVertexerTracks E. Bruna (TO), E. Crescio (TO), A. Dainese (LNL), M. Masera (TO), F. Prino (TO)
FTPC status and results Summary of last data taken AuAu and dAu calibration : Data Quality Physic results with AuAu data –Spectra –Flow Physic results.
Secondary Vertex reconstruction for the D + Elena Bruna University of Torino ALICE Physics Week Erice, Dec. 6 th 2005.
Jet Physics at CDF Sally Seidel University of New Mexico APS’99 24 March 1999.
1 SDD offline status Francesco Prino INFN sezione di Torino ALICE offline week – March 15th 2010.
First measurements in Pb—Pb collisions at  s NN =2.76 TeV with ALICE at the LHC M. Nicassio (University and INFN Bari) for the ALICE Collaboration Rencontres.
Muon detection in NA60  Experiment setup and operation principle  Coping with background R.Shahoyan, IST (Lisbon)
Detector alignment Stefania and Bepo Martellotti 20/12/10.
D 0 reconstruction: 15 AGeV – 25 AGeV – 35 AGeV M.Deveaux, C.Dritsa, F.Rami IPHC Strasbourg / GSI Darmstadt Outline Motivation Simulation Tools Results.
K 0 s reconstruction in ALICE Giuseppe Lo Re INFN, Sezione di Catania, and Dipartimento di Fisica e Astronomia, Università di Catania, Italy, March 2002.
Using Track based missing Et tools to reject fake MET background Muhammad Firdaus Mohd Soberi UMichigan-CERN Semester Program Thursday, 12 th February.
CMS Upgrade Workshop - Fermilab Trigger Studies Using Stacked Pixel Layers Mark Pesaresi
4/12/05 -Xiaojian Zhang, 1 UIUC paper review Introduction to Bc Event selection The blind analysis The final result The systematic error.
Heavy stable-particle production in NC DIS with the ZEUS detector Takahiro Matsumoto, KEK For the ZEUS collaboration.
Vertex Reconstruction for High Luminosity pp Running at STAR STAR-Spin luminosity requirements Method of the vertex reconstruction Application to the pileup.
A. Pulvirenti - Resonances measurement in pp and PbPb with ALICE 1 Outline The Study of Short-Lived Resonances with the ALICE Experiment at the LHC Ayben.
Impact Parameter Resolution Measurements from 900 GeV LHC DATA Boris Mangano & Ryan Kelley (UCSD)
Paolo Massarotti Kaon meeting March 2007  ±  X    X  Time measurement use neutral vertex only in order to obtain a completely independent.
Tau31 Tracking Efficiency at BaBar Ian Nugent UNIVERSITY OF VICTORIA Sept 2005 Outline Introduction  Decays Efficiency Charge Asymmetry Pt Dependence.
Status of the measurement of K L lifetime - Data sample (old): ~ 440 pb -1 ( ) - MC sample: ~125 pb -1 ( mk0 stream ) Selection: standard tag (|
D. Elia (INFN Bari)ALICE Offline week / CERN Update on the SPD Offline Domenico Elia in collaboration with H. Tydesjo, A. Mastroserio Overview:
Pattern recognition with the triplet method Fabrizio Cei INFN & University of Pisa MEG Meeting, Hakata October /10/20131 Fabrizio Cei.
INFN - PadovaBeauty Measurements in pp with the Central Detector 1 Beauty Measurements in p-p with the Central Detector F. Antinori, C. Bombonati, A. Dainese,
January 2009 offline detector review - 2 nd go 1 ● Offline – Geometry – Material budget – Simulation – Raw data – OCDB parameters – Reconstruction ● Calibration.
Time-zero evaluation using TOF, T0 and vertex detectors
y x Vincenzo Monaco, University of Torino HERA-LHC workshop 18/1/2005
Calibration: preparation for pa
Full Sim Status Estel Perez 27 July 2017.
New TRD (&TOF) tracking algorithm
Technical Specifications
Using IP Chi-Square Probability
M. Kuhn, P. Hopchev, M. Ferro-Luzzi
SCT readout limitation estimate with data
Massimo Masera INFN sezione di Torino
Beam Gas Vertex – Beam monitor
Charged-particle multiplicity with ALICE at LHC
Workshop “MC for the LHC” - CERN
Analysis Test Beam Pixel TPC
Michele Pioppi* on behalf of PRIN _005 group
5% The CMS all silicon tracker simulation
Hadronic resonances from ALICE in pp collisions
The LHC collider in Geneva
p0 life time analysis: general method, updates and preliminary result
Quarkonium production in ALICE
Reddy Pratap Gandrajula (University of Iowa) on behalf of CMS
Hadronic resonances from ALICE in pp collisions
Reconstruction of short-lived resonances in pp collisions
Using Single Photons for WIMP Searches at the ILC
Perspective for the measurement of D+ elliptic flow
Prospects for quarkonium studies at LHCb
The LHCb Level 1 trigger LHC Symposium, October 27, 2001
Contents First section: pion and proton misidentification probabilities as Loose or Tight Muons. Measurements using Jet-triggered data (from run).
Dilepton Mass. Progress report.
Measurement of long-range correlations in Z-boson tagged pp collisions
p0 ALL analysis in PHENIX
Status of the cross section analysis in e! e
Presentation transcript:

Primary vertex reconstruction with the SPD E. Crescio, M. Masera, F. Prino INFN and Università di Torino A. Dainese INFN LNL ALICE PHYSICS WEEK – Münster – February 12th 2007

Outline Summarize status of SPD vertexing algorithms AliITSVertexerZ AliITSVertexer3D Show recent modifications/upgrades AliITSVertexer3D is relatively new (first version commited to CVS on October 30th 2006) and is still under development/optimization Answer to specific issues arisen in First Physics meeting of January 19th 2007 Vertexeing with tracks not discussed see talk by A. Dainese on Friday

AliITSVertexerZ – the method Build “tracklets” from SPD Clusters associate each Cluster on layer1 to all the Clusters on layer2 within a window Δφ <0.01 rad Calculate Zi = Z of closest approach of tracklet and nominal beam axis. Fill a histogram of Zi with 100 mm (200 in pp) bin size define a z window (2 mm wide) around the “peak” Calculate vertex position and error Zv = weighted average of the Zi of the tracklets in the window after symmetrization around the peak Error = propagation of errors on Clusters also in case of just 1 tracklet Layer 2 Layer 1 Beam axis HijingParam1500  New version, committed to CVS on Feb. 9th

Z distributions for single events: examples p-p event Z distributions for single events: examples signal Combinatorial background Higher multiplicity event (Hijing parametrized with 1500 charged primary particles in 2 units of rapidity)

Vertexer3D – the method Build tracklets (= straight lines) from pairs of Clusters on layers 1, 2 First selection done w.r.t. nominal beam axis Loose selection: Δφ < 0.5 rad, DCA to beam < 2.5 cm, |zINT|<5.3 cm Combine tracklet pairs and select them according to: small DCA (< 1 mm) between the two tracklets Tracklet intersection close to beam axis (rINT < 2.5 cm ) Tracklet intersection in the diamond region (zINT< 5.3 cm) Get a first estimate of the vertex from selected tracklets same vertex finder algorithm used with ESD tracks (AliVertexerTracks) Re-build tracklets Selection done w.r.t. beam position from vertex estimate in previuos step Tight selection: Δφ < 0.01 rad, DCA to beam < 0.5 cm, |zINT - zVERT|<0.5 cm small DCA (<1 mm) between the two tracklets Tracklet intersection close to the estimated vertex (Dr < 0.5 cm) Tracklet intersection in the diamond region (Dz < 0.5 cm) Calculate the vertex using the selected tracklets

Events used in this study Event generation AliRoot v4-04-Release of June 2007 pp collisions (kPyMb) at s=14 TeV Vertex smearing on x,y (50 mm) and z (5.3 cm) NO TRIGGER information 4 sets of pp events: 9800 events with beam centered in (0, 0) 9400 events with beam centered in (500 mm, 0) 9200 events with beam centered in (5 mm, 0) 10000 events with beam centered in (1 cm, 0) VertexerZ and Vertexer3D performance studied in bins of Ntracklets in SPD (AliMultiplicity::GetNumberOfTracklets) Last version of AliMultiplicity on CVS gives the number of associated Clusters as discussed on January 19th meeting

Overall efficiency Efficiency = Number of event with vertex / Total number of events Vertexer3D efficiency increased by ≈4% with DCA cut optimization Vertexer3D requires at least 2 selected tracklets Events with just one tracklet are ≈10% VertZ Vert3D kPyMb 84% 72% Non diffr. 98% 90% Single Diffr. 53% 33% Double diffr. 57% 32%

More on efficiency GetNContributors() for VertexerZ information on where inefficiencies come from: >0  Vertex OK (≈84% of events) 0  error in the vertex finding procedure (0%) -1  no tracklets (≈0.25%) -2  no Clusters in 1 SPD layer (≈16%)

Residuals Zfound – Ztrue distribution for VertexerZ in the 6 multiplicity bins Good agreement between gaussian sigma and histo RMS

VertexerZ: average of residuals Unbiased! The small bias (≈5 mm) which was present in the previous releases of the code was due to a systematic error in finding the maximum of the histograms for few low multiplicity events Corrected since Rev. 1.17 of AliITSVertexerZ.cxx

Vertexer3D: average of residuals No apparent bias

Resolutions Resolution improved for both vertexers in last weeks New procedure for VertexerZ Cut optimization for Vertexer3D

Pulls Distributions of (Zfound-Ztrue)/Zerr Only for VertexerZ, error calculation for Vertexer3D still under development

VertexerZ: pulls Pull distribution has RMS ≈ 1.5 independent of multiplicity Checked also with higher multiplicity events Errors slightly underestimated Other sources of error: Multiple scattering (Beam Pipe +Layer 1)  found to be negligible Beam smearing effect (see next slide) Error on radius (under study)

Beam smearing contribution HijingParam generation with 500 particles in |y|<2 Beam X,Y smearing = 50 mm Pull = 1.5 Beam X,Y smearing = 0 Pull = 1.36

VertexerZ vs. vertex position (I) Efficiency and RMS worsen for large | zvertex| Due to smaller number of tracklets in acceptance Average of residual stable against zvertex No bias as a function of zvertex

Ntracklets vs. Ztrue SPD extends from z=-14 cm to z= 14 cm For |Zvertex| >≈ 14 cm the number of SPD tracklets (and ESD tracks with SPD points) starts to decrease

VertexerZ vs. vertex position (II) In events generated with AliRoot rev. after June 12th 2006 a bias (slope vs. ztrue) is observed see Jan Fiete talk at first physics meeting on Jan 19th 2007 Major modifications in ITS geometry ITS geometry changed to TGeo SPD chip thickness reduced to 150 mm The bias is introduced by the SPD chip thickness Bug found and fixed by L. Gaudichet on February 5th 2007

Beam offset in X and Y VertexerZ resolution dramatically worsens in case of large (and unknown) beam offset The performance is completely recovered if the X,Y position of the beam is known Vertexer3D performance not affected also in case of large and unknown beam offset

Summary Vertexer Z (items under study are in red color) Very high overall efficiency (98% for non diffractive events) Inefficiencies essentially due to events with no Clusters on SPD layer 2 Suitable for all multiplicities --> p-p ; p-A; Pb-Pb interactions No bias Error calculated for all events but slightly underestimated (pulls≈1.5) Performance dramatically worsens with increasing X,Y beam offset If the X,Y position of the beam is known the performance is completely recovered Under study the application for pile-up detection Vertexer3D (items under study are in red color) Efficiency limited by the need of at least 2 tracklets Performance remains practically the same also for large beam offsets CPU time and memory consumption presently under test Important for application to Pb-Pb interactions Error calculation under study (VertexFitter of AliVertexerTracks should be used) Under study the application for measuring average x,y beam position in the LHC fill

Backup slides

VertexerZ and beam offset (I) Beam offset up to 1 cm assumed unknown Efficiency not affected Resolution dramatically worsens with increasing beam offset

VertexerZ and beam offset (II) Beam offset up to 1 cm assuming to know the beam position Good performance for offsets up to 1 cm if the beam position is known

Vertexer3D and beam offset Beam offset up to 1 cm assumed unknown Performance maintained

Efficiency – detail (Z)

Residuals 3D (X)

Residuals 3D (Y)

Residuals 3D (Z)

VertexerZ at higher multiplicities

VertexerZ at higher multiplicities

VertexerZ at higher multiplicities

Pile-up Expected interaction rate = 2×105 Hz at a luminosity of 5×1030 cm-2s-2 1 interaction every 200 bunch crossings In case of SPD strobe duration of 100 ns 4 bunch crossings (0.02 interactions) All events in the strobe are overlapped even if not belonging to the same bunch-cross Caveat: high- multiplicity triggers will select piled-up events First check on AliITSVertexerZ in the case of pile-up “Manual merging” of recpoints with an “ad hoc” macro Results: Vertices with distances >600 μm: the vertex of the event with higher multiplicity is found Vertices with distances <600 μm: an intermediate value of z is found Under study: check if the vertexer can be used to “detect” the pile-up, searching for two peaks (possible in the case of well separated peaks) Study to be performed also on the Vertexer3D