status of fast tracking algorithm mdchough
DESCRIPTION
Status of Fast Tracking Algorithm MdcHough. Guowei YU 8 th March 2006. Outline. Introduction MdcHough Algorithm Results and Discussions Summary. Introduction. Algorithm Developments in MDC Reconstruction Presented by W.D.Li ,Migrated from ATLAS. Purpose Efficient track finding - PowerPoint PPT PresentationTRANSCRIPT
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Status of Fast Tracking Algorithm MdcHough
Guowei YU
8th March 2006
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Outline
Introduction
MdcHough Algorithm
Results and Discussions
Summary
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Introduction Algorithm Developments in MDC Reconstruction
Presented by W.D.Li ,Migrated from ATLAS
Developer Offline Algorithm Events filter
AlgorithmS.L.Zang Mdc Tracking
Y.Zhang MdcPatRec
X.M.Zhang MdcFastTrk
G.W.YU MdcHough
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Purpose Efficient track finding Nice transverse momentum resolution High efficiency of track finding at high noise level
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MdcHough Algorithm
43 layers,19 axial type|cos|<0.93Cell is near square ~8.1mm
Interaction point
Cosθ=0.83
Cosθ=0.93
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Flow of MdcHough
Hits PT
Initial track finding
Local maximum finding
Track selection and Merging
Track fitting
MdcHough
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Initial track finding (use a LUT-base Hough Transform) (R,) (,1/pT) [(0~2) pT (400MeV~)]
qCTR=sin (–0) CT= 0.3/pT
Build a wire-ordered look-up table ( 1/pT= 300 100)
.
wire n+1
wire n
active wire n-1
wire .
.
. .
Bin 1 Bin 2 … Bin 100
Bin 1 Bin 2 … Bin 100
Bin 1 Bin 2 … Bin 100
.
wire-ordered
LUT
Flow of MdcHough
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Local maximum finding (select good track candidates by wired-oreded LUT)
Track selection and Merging Nhit > 15 Merge some tracks sharing more th
an 9 hits
Flow of MdcHoughFlow of MdcHough
15 15 1616 18 1713 14 14
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Track fitting Obtain hits from Bin-ordered LUT Fitting track to get PT by using lpav tool
.
bin n+1
bin n
bin bin n-1
number .
.
. .
wire 1 wire 2 … wire 19
wire 1 wire 2 … wire 19
wire 1 wire 2 … wire 19
.
bin-ordered
LUT
Flow of MdcHoughFlow of MdcHough
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Results and Discussion Track Reconstruction CPU
Time ~ 1ms/1 track Resolution of PT(1.0GeV )
Generate (PT :1GeV) by Fixpt Efficiency of Reconstruction
() VS cos(polar angular)
p=8.0 MeV
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Efficiency of Reconstruction VS PT( e p)
Momentum resolution VS PT (μ,e,π,p) Double Gauss Fit
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Noise level type 0: = C type 1: 1/r type 2: 1/r2 (PT:1.0GeV )
Efficiency vs noise Resolution VS noise
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Summary It costs about 1ms to reconstruct 1 track Efficiency of reconstruction() : >99% (PT>300MeV) for single track >99% when noise level are 5%,10% ,15% and 20% decrease quickly when polar angular more than 0.8 Resolution of momentum(p): PT < 1.0GeV p of proton is more than others
PT > 1.0GeV p keeps about same value for all particles p turns bad at noise level is more than 10% in type “0” Same results by adding wires shift; Further work is to enhance near polar angular and test the Algorithm
in adjusted magnetic field
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Thank!