Gammapi0 discrimination using ALICEEMCAL

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Gamma-pi0 discrimination using ALICE-EMCAL
Why Gamma-Jet pi0 leading particle Jet (after
suppression) Direct photons
Analysis in Jet Level Isolation (Et(cluster)
et(jetcone) lt threshold)) No Tracks within cone
Discussion here single cluster level,
gamma/pi0?
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Approaches (i) One dimensional shower shape
analysis (ii) Principal Component Analysis (iii)
Artificial Neural Network
Tools (i) Galice.root, Digits file from Alexie
(ii) Single particles 1000 evnts, one Hijing
event (iii) Clusterization and reconstruction of
point (issue of threshold) (iv) Evaluate
various parameters (Dispersion, ellipse
axes, energy etc) (v) Use discriminatory
properties
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Some QA (HIT Level)
Nhits (10 GeV gamma)
Pi0, 10 GeV
Phi-Phi(centroid)
gamma(10)
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DIGITS
Digits from 10 GeV Photon
Number of digits (from 10 hits)
Digit Amplitude
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CLUSTERS
Clusters are contiguous towers above
threshold. Threshold Pedestal and background
threshold Mostly 300 MeV Reconstructed Points
energy, Digits shape parameters
20 GeV gamma
Find the Point with maximum energy
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Gamma (5)
Gamma( 20)
Pi0 (20)
pi0(5)
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Shape parameters (lambda0) (Gamma)
Pi0
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With Hijing
One Hijing Event is taken and digitised Phton
events are superposed on Hijing events depending
on SuperModule, and Id of Towers
With a cutoff of 300-500 MeV, discrimination does
not get affected drastically.
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Gamma-Pi0 discrimination (2 x 2 geometry)
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Gamm-pi0 discrimination (3 x3 geometry)
2x2
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Summary and Plan
g-p0 Discrimination performed in AliRoot
framework Geometry with projection in Eta and
different granularity studied. Only 1-D shower
shape analysis used.
Plan immediate Apply Neural Network with
shower-shape as Input Study the effect of
various thresholds not-so-immediate Superpose
Pythia Jets (gamm-jet, leading pi0 jets) on
Hijing and study full jet reconstruction.