em scale using h ’s
DESCRIPTION
EM scale using h ’s. Vishnu V. Zutshi BNL. Preamble. gg decays Important for absolute calibration Non-linearity and offsets Maybe possible with little or no trigger Maybe possible with little or no tracking Affords the possibility of refinement Testing ground for Monte Carlo. - PowerPoint PPT PresentationTRANSCRIPT
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EM scale using ’s
Vishnu V. Zutshi
BNL
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Preamble
decays Important for absolute calibration Non-linearity and offsets Maybe possible with little or no trigger Maybe possible with little or no tracking Affords the possibility of refinement Testing ground for Monte Carlo
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Schematic
2 peaks and a valley EM3 is your best chance here Neighbourhood definition You may or may not want to extend the
EM3 clustering to other floors CellNN does extend it to other floors
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CellNN
• Each local maxima starts a floor cluster
• An EM cell is defined to have 4 neighbours
• Log weighting for position determination
• Sharing based on a transverse parameterization of the shower
• Angular matching between floor clusters
• Position measurement is key
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Just maybe
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5 GeV ’s
Asym=abs(e1-e2)/(e1+e2)
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Single photons
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5 GeV ’sun
corr
ecte
dcorrected
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5 GeV ’s
+ E corr.
+ Asym. cut
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5 GeV ’sLower Fcluster threshold
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5 GeV ’sLower Fcluster threshold
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1 GeV photon
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2 GeV photons
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10 GeV ’s
E/Egen
Ene
rgy
mat
chin
g
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10 GeV ’s
E/Egen
unco
rrec
ted corrected
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10 GeV ’s
deltaR=sqrt()
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5 GeV ’s
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5 GeV ’sLower Fcluster threshold
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10 GeV ’s
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10 GeV ’sP
ositi
on d
eter
min
ed f
rom
ly3
if e
mfr
>0.
2
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10 GeV ’s
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Single photons
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10 GeV ’sL
y3fr
ac>
0.2
and
new
W0’
s
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10 GeV ’s
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5 GeV ’s
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Ongoing…
• W0’s for Fclustering
• Energy corrections
• Fthreshold
• Neighbourhood
• Sharing
• Symmetric mass