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ITS Algorithm Review Introduction

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ITS Algorithm Review. Introduction. A. Badala', R. Barbera, B. Batyunya, Y. Belikov, M. Bondila, ... Geometry R. Barbera (afternoon) SPD T. Virgili (B. S. ... – PowerPoint PPT presentation

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Title: ITS Algorithm Review Introduction


1
ITS Algorithm ReviewIntroduction
  • A. Badala, R. Barbera, B. Batyunya, Y. Belikov,
    M. Bondila,
  • N. Bustreo, R. Caliandro, P. Cerello, E. Crescio,
    R. Fini,
  • E. Fragiacomo, J. Hubbel, E. Lopez, G. Lo Re, M.
    Masera, B. S. Nilsen,
  • G. S. Pappalardo, A. Pulvirenti, W. Peryt, S.
    Radomski, F. Riggi,
  • T. C. Randles, P. Skowronski, R. Turrisi, L.
    Vannucci, T. Virgili.

2
Agenda
  • Introduction B. S. Nilsen
  • Infrastructure-Organization. B. S. Nilsen
  • Geometry R. Barbera (afternoon)
  • SPD T. Virgili (B. S. Nilsen)
  • SDD P. Cerello
  • SSD E. Fragiacomo
  • Tracking A. Badalá/Y. Belikov
  • PID B. Batyunya

3
ITS Algorithm ReviewInfrastructure - Organization
  • by
  • Bjørn S. Nilsen

4
Philosophy
  • Keep it as general as possible
  • ITS geometry has gone through many changes
  • Simulations?Reconstruction has maximum
    flexibility
  • Keep things modular
  • Easier to make changes
  • Minimize code duplication

5
Which are theNon-general Routines
  • AliITSv
  • Defines Geometry/Material of the ITS
  • AliITSsegmentation
  • Defines Geometry of detector layout
  • AliITSresponse
  • Defines electrical and related properties
  • AliITSClusterFinder
  • First level Reconstruction

6
One Last Assumption
Z axis same direction as ALICE Z axis.
Violated by AliITSv3.
7
Order of Operations
  • AliRunInitMC
  • Executes Config.C
  • Defines gMC AliGeant3()
  • Defines all detectors new AliITSvPPRasymm()
  • gMC-gtInit
  • For each Detector
  • Create Materials AliITSCreateMaterials
  • Create Geometry AliITSCreateGeometry
  • FinishGeometry
  • For each Detector
  • Detector-gtInit AliITSvPPRasymmInit
  • Sets up and fills AliITSgeom class (GEANT3.21
    only), Optionally may read or write AliITSgeom
    to/from file.
  • Sets default segmentation, response, but not
    simulation or reconstruction (at present). See
    later.
  • Init for Step Manager, sensitive volume
    (AliITSInit) and ITS mother volume
    (AliITSvPPRasymmInit) ID numbers.
  • Detector-gtBuildGeometry AliITSBuildGeometry

8
Comments about Materials
galice.cuts ? Config.C only ?
30KeV e- in Si has a range of 14µm
? In Config.C
9
Still some moreabout materials
10
Detector Simulations
  • AliITS(TObjArray) fDetType one for each
    detector type.
  • AliITSDetType classes.
  • AliITSresponce fResponce
  • AliITSsegmentation fSegmentation
  • AliITSsimulation fSimulation
  • AliITSClusterFinder fReconst
  • And the Digit and Cluster branch names
  • Default values set in AliITSvPPRassymInit().

11
Hits to SDigits/Digits
  • Set default or other simulation, get default or
    change response and segmentation classes for each
    detector.
  • Set up SDigits or Digits Tree.
  • All hits copied into memory sorted by module.
    AliITS(TObjArray) fITSmodules one for each
    module 2198.
  • AliITSmodule
  • Module index number ? Layer, Ladder, Detector ?
    Detector type
  • TObjArray of hits
  • Arrays of track index and hit index numbers
  • The location in the TreeH of a specific hit.
  • Merging at hit level easy. Just add new hits to
    their module.
  • Size of Hitnumber of hits lt Size of
    SDigitNumber of SDigits.
  • Loop over these modules
  • Determine detector type (SPD,SDD,SSD,)
  • Get copy of simulation, response, and
    segmentation
  • Execute simulation to make SDigits or Digits.
  • SDigits and/or Digits automatically sorted by
    module.

12
SDigits to DigitsUses SDigit Merger
  • Set default or other simulation, get default or
    change response and segmentation classes for each
    detector.
  • Must be the fully compatible with that used in
    Hits To SDigits!
  • Set up Digits Tree.
  • Read in SDigits (already module ordered).
  • Loop over these modules/SDigits
  • Determine detector type (SPD,SDD,SSD,)
  • Get copy of simulation, response, and
    segmentation
  • Execute simulation to make Digits.
  • Digits automatically sorted by module.
  • Merger loops over SDigit files. The first file
    processed can be used to set up a region of
    interest cut.

13
Comments on Digits
  • Each detector type defines its own digit.
  • For each detector, there are two type of digits.
  • Basic Digit. Same for all detectors
  • Int_t fCoord1 SPD, SDD z cell number SSD P/N
    layer.
  • Int_t fCoord2 SPD, SDD x cell number SSD strip
    number.
  • Int_t fSignal SDD, SSD ADC value, SPD 1
  • Simulation Digit. Detector specific
  • SPD Array of track index and hit index
    numbers, signal in SPD cell (Int_t electrons).
  • SDD Array of track index and hit index
    numbers, signal in SDD cell per track (Float_t
    electrons), and the signal the dominant particle
    contributes to the total signal.
  • SSD Array of track index and hit index
    numbers.

14
ReconstructionDigits to RecPoints
  • Set default or other ClusterFinder
    (reconstruction), get default or change response
    and segmentation classes for each detector.
  • Should be the fully compatible with that used in
    Hits To SDigits or Hits To Digits
  • Set up RecPoint Tree.
  • For each module.
  • Read in this modules digits
  • Determine which detector
  • Perform the Digits to RecPoints

15
Comments onAliITSgeom class
  • Consists of
  • TObjArray of AliITSgeomMatrix class members.
  • Transformation from detector local coordinates
    (x,y,z) to global coordinates.
  • Minimal set of functions exclusively used via
    AliITSgeom class.
  • Number of layers, ladders per layer, detectors
    per ladder, and the total number of modules.
  • Flag to describe transformation type. Default
    GEANT.
  • TObjArray of the types of shapes of each
    detector.
  • Large set of functions related to geometry and
    coordinate transformations. Some just repackage
    AliITSgeomMatrix classes.
  • Primarily motivated by needs of ITS Alignment
    work.

16
Fast Simulation-Reconstruction
  • Takes hits, smears position, generates RecPoints.
  • Position smearing s need review.
  • Overlapping tracks have perfect separation.
  • Signal effects, noise, response, dead-channels,
    Not taken into effect.
  • Uses the same RecPoint data structure as the slow
    simulation.
  • Used by some groups. They must verify its
    validity, we will not.

17
Macros
  • Simulation and Reconstruction Macros
  • AliITSHits2SDigits.C
  • AliITSMerge.C
  • AliITSDigits2RecPoints.C

18
SPD simulation
  • Tiziano Virgili
  • University of Salerno
  • Present by
  • Bjørn S. Nilsen

19
Content
  • The Model.
  • What is new.
  • Results from simulation.
  • Comparison with Experimental data.

20
The model
  • Two models are available.
  • Bari/Salerno (default)
  • Geometrical charge sharing.
  • Noise and threshold fluctuations.
  • Coupling effects.
  • Dubna
  • Geometrical charge sharing.
  • Charge diffusion.
  • Noise and threshold fluctuations.

21
Geometrical Charge Sharing
  • Find points where particle crosses pixel
    boundaries.
  • Distribute energy/charge according to fraction of
    that between boundaries.

22
Simulation Parameters
  • Threshold 2000 e
  • Noise s280 e
  • No noise appears above threshold
  • No Coupling used.
  • 1 dead pixels, random.

23
Test Beam Comparison
  • The Bari-Salerno model (FORTRAN version) is used
    by NA57.
  • The number of single pixel clusters simulated is
    more than seen in the Test Beam data.
  • The number of 2 and more wide pixels are greatly
    under predicted.

Bari-Salerno Dubna Test Beam
24
Test Beam ComparisonsProblems cont.
  • Adjusting parameter of the Dubna model can
    compensate a bit, but leads to unphysical
    diffusion parameters.
  • Changes to the Bari-Salerno model would require
    similarly unphysical asymmetric coupling
    parameters.

Bari-Salerno Dubna Test Beam
25
Final Comments
  • New ALICE1 chip will be used (not used in NA57)
  • Lower noise, thresholds,
  • Introducing coupling will increase 3 pixel
    clusters and not 2 pixel clusters (unless the
    coupling is non-symmetric).
  • Diffusion exists and so the Dubna model needs to
    be reintroduced with some new modifications (work
    under way).
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