Update on hyperon (Lambda0 - AntiLambda0) simulations with ...€¦ · Update on hyperon (Lambda0 -...
Transcript of Update on hyperon (Lambda0 - AntiLambda0) simulations with ...€¦ · Update on hyperon (Lambda0 -...
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N.DIVANI - GSI & HIM 1
Update on hyperon (Lambda0 - AntiLambda0) simulations with the PANDA GEM-Tracker
Nazila Divani,
Radoslaw Karabowicz, Takehiko R. Saito, Bernd Voss
Helmholtz Center for Heavy Ion Research (GSI)
Helmholtz Institute Mainz (HIM)
PANDA Collaboration Meeting 17/2 – GSIPANDA Collaboration Meeting 17/2 – GSI 6-9 June 2017
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N.DIVANI - GSI & HIM 2
Motivation
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
● To investigate the invariant mass reconstruction for the anti-p + p 0 + anti- 0 as a ⟶∧ ∧important hyperonic channel using PANDA GEM-Tracker.
● This channel has been chosen since Lambda is the lightest hyperon, which is easiest to produce and all final state particles are charged and most of them are flighted in the forward directions.
Benchmark channel including : antip + p → 0 Λ + anti 0Λ0 Λ p+ & – → π
Anti 0 Λ p & +→ π
The exact mass value of the 0Λ and anti 0Λ 1115.683±0.006MeV/c²
In continuous of my two previous presentations ( PCM LVIII (results for the Realistic P.R. and Isotropic D.)
& PCM 17/1 (results for the Realistic P.R. and Boosted D.) ):
To show the recent results
- Using Idealistic Pattern Recognition
- In the case of the Forward Peaking (Boosted Distribution)
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N.DIVANI - GSI & HIM 3
Reminder: Investigation of Lambda – Anti Lambda Invariant Mass Reconstruction with PANDA GEM-Tracking Detector (Realistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
The simulation conditions: No. of Events=10000 SimEngine =TGeant4 Event generator=EvtGenDirect Beam Momentum= 2 [GeV/c] lambda0_antilambda0_piminus_p_piplus_antip.dec (LambdaLambdaBar sitting beam momentum) Boosted distribution (forward peaking) PANDA setup without and with full geometry of the GEM Using PndBarrelTrackFinder (realistic pattern recognition) For Tight PID: using “PidAlgoMVD, STT, DRC, DISC, EMC, MDT, TOF” and “PidAlgoIdeal” Using Revision 29629 of PandaRoot
Updated Geomatry : gem_3Stations_realistic_v2.root
gem_3Stations_realistic_v2.digi.par
Covering Polar Angles: about 222 degrees in forward directions
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N.DIVANI - GSI & HIM 4
Beam Momentum=2GeV/c, Boosted distribution (Forward Peaking), Mass Reconstruction,Using PndBarrelTrackFinder (Realistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
Eff.:26.6%>15.4%
Eff.:51.1%>19.1% Eff.:3.1%>1.9%
Eff.:5.7%>4.4%
Eff.:21.1%>6.4%
Eff.:12.7%>8.5%
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N.DIVANI - GSI & HIM 5
Beam Momentum=2GeV/c, Boosted distribution (Forward Peaking), Tight PID, Theta DistributionUsing PndBarrelTrackFinder (Realistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
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N.DIVANI - GSI & HIM 6
Beam Momentum = 2GeV/c , Boosted distribution (Forward Peaking), Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
The simulation condition: No. of Events=10000 SimEngine =TGeant4 Event generator=EvtGenDirect Beam Momentum= 2 [GeV/c] lambda0_antilambda0_piminus_p_piplus_antip.dec (LambdaLambdaBarsitting beam momentum) Boosted distribution (forward peaking) PANDA setup without and with full geometry of the GEM Using PndSttMvdGemTrackingIdeal (idealistic pattern recognition) For Tight PID: using “PidAlgoMVD, STT, DRC, DISC, EMC, MDT, TOF” and “PidAlgoIdeal” Using Revision 29629 of PandaRoot
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N.DIVANI - GSI & HIM 7
Beam Momentum=2GeV/c, Boosted distribution (Forward Peaking), momentum vs theta,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
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N.DIVANI - GSI & HIM 8
Beam Momentum=2GeV/c, Boosted distribution (Forward Peaking), Mass Reconstruction,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
Eff.:47.7%>17.0%
Eff.:14.6%>5.9% Eff.:37.7%>13.0%
Eff.:27.1%>11.0% Eff.:39.2%>15.4%
Eff.:54.0%>19.2%
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N.DIVANI - GSI & HIM 9
Beam Momentum=2GeV/c, Boosted distribution (Forward Peaking), Tight PID, Theta Distribution,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
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N.DIVANI - GSI & HIM 10
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
Summary
- Study about forward peaking using idealistic pattern recognition is done. - Using GEM has a good improvement for Anti-Lambdas mass reconstruction. - Lambdas come from low momentum tracks and they have a large angular distribution.
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N.DIVANI - GSI & HIM 11
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
Spare
More Results
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N.DIVANI - GSI & HIM 12
Beam Momentum=2GeV/c, Isotropic distribution, Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
The simulation condition: No. of Events=10000 SimEngine =TGeant4 Event generator=EvtGenDirect Beam Momentum= 2 [GeV/c] lambda0_antilambda0_piminus_p_piplus_antip.dec Isotropic distribution PANDA setup without and with full geometry of the GEM Using PndSttMvdGemTrackingIdeal class (idealistic pattern recognition) For Tight PID: using “PidAlgoMVD, STT, DRC, DISC, EMC, MDT, TOF” and “PidAlgoIdeal” Using Revision 29629 of PandaRoot
![Page 13: Update on hyperon (Lambda0 - AntiLambda0) simulations with ...€¦ · Update on hyperon (Lambda0 - AntiLambda0) simulations with the PANDA GEM-Tracker Nazila Divani, Radoslaw Karabowicz,](https://reader033.fdocuments.in/reader033/viewer/2022053100/605847b4a04ba37bcf7ce54c/html5/thumbnails/13.jpg)
N.DIVANI - GSI & HIM 13
Beam Momentum=2GeV/c, Isotropic distribution, momentum vs theta,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
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N.DIVANI - GSI & HIM 14
Beam Momentum=2GeV/c, Isotropic distribution, Mass Reconstruction,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017
Eff.:58.2%>21.7%
Eff.:35.8%>12.9%
Eff.:38.2%>13.5%
Eff.:47.4%>19.0%
Eff.:49.6%>20.1%
Eff.:58.4%>21.0%
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N.DIVANI - GSI & HIM 15
Beam Momentum=2GeV/c, Isotropic distribution, Tight PID, Theta Distribution,Using PndSttMvdGemTrackingIdeal (Idealistic Pattern Recognition)
PANDA Collaboration Meeting 17/2, GSI, PANDA Collaboration Meeting 17/2, GSI, 6-9 June 2017