GEM DHCAL

1
GEM-DHCal Performance and Energy Flow Algorithm
Studies
ALCW 2004, SLAC Jae YuUniversity of Texas at
Arlington

• Single Pion Performance Study
• Study of Pythia events
• Energy Flow Algorithm
• Single pion Track cluster matching studies
• Conclusions

On behalf of the HEP group at UTA.
2
Introduction

• DHCAL a solution for keeping the cost manageable
  for EFA
• Finer cell sizes are needed for efficient
  calorimeter cluster association with tracks and
  subsequent energy subtraction
• UTA focused on DHCAL using GEM for
• Flexible geometrical design, using printed
  circuit pads
• Cell sizes can be as fine a readout as GEM
  tracking chamber!!
• High gains, above 1034,with spark probabilities
  per incident ? less than 10-10
• Fast response
• 40ns drift time for 3mm gap with ArCO2
• Relatively low HV
• A few 100V per each GEM gap
• Possibility for reasonable cost
• Foils are basically copper-clad kapton
• 3M produces foils in large quantities (12x500ft
  rolls)

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UTA GEM Simulation

• Use Mokka as the primary tool
• Kept the same detector dimensions as TESLA TDR
• Replaced the HCAL scintillation counters with GEM
  (18mm SS 6.5mm GEM, 1cmx1cm cells)
• Single Pions used for initial studies
• 3 100 GeV single pions
• Analyzed them using ROOT
• Compared the results to TDR analog as the
  benchmark
• GEM Analog and Digital (w/o threshold)
• ECal is always analog

4
UTA Double GEM Geometry
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Performance Comparisons of Detailed and Simple
GEM Geometries
Detailed GEM 75GeV p
Simple GEM 75GeV p
ltEgt0.81 ? 0.008MeV
ltEgt0.80 ? 0.007MeV

• 25.2sec/event for Simple GEM v/s 43.7 sec/event
  for Detailed GEM
• Responses look similar for detailed and simple
  GEM geometry
• Simple GEM sufficient

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GEM-Digital Elive vs of hits for p-
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EM-HCAL Weighting Factor

• ELiveSEEM W SGEHCAL
• For analog
• L G is used to determine the mean values as a
  function of incident pion energy for EM and HAD
• Define the range for single Gaussian fit using
  the mean
• Take the mean of the Gaussian fit as central
  value
• Choose the difference between G and LG fit means
  as the systematic uncertainty
• For digital
• Gaussian for entire energy range is used to
  determine the mean
• Fit in the range that corresponds to 15 of the
  peak
• Choose the 15 G fit mean as the central value
• Difference between the two G as the systematic
  uncertainty
• Obtained the relative weight W using these mean
  values for EM only v/s HCAL only events
• Perform linear fit to Mean values as a function
  of incident pion energy
• Extract ratio of the slopes ? Weight factor W
• E C ELive

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Response - Comparison
9
GEM Analog Digital Converted 15 and 50 GeV p-
50GeV Analog
15GeV Analog
15GeV Digital
50GeV Digital
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Resolution - Comparison
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GEM Performance Study Summary

• GEM digital and analog responses comparable
• Large remaining Landau fluctuation in analog mode
  observed
• Digital method removes large fluctuation ? Become
  more Gaussian
• GEM Energy resolutions
• Digital comparable to TDR
• Analog resolution worse than GEM digital or TDR
• GEM is as good a detector as others for DHCAL

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Does more Gaussian Behavior of GEM digital make
sense?

• Gas detectors have small number of primary
  ionization electrons ? Very Landau like
  distributions
• Large amplification only stretches out the Landau
  distribution
• Amplification does not increase the number of
  primary electrons
• It only worsens the fluctuation
• The cells with large energy due to the
  fluctuation get saturated
• Suppressing the large energy tail
• While preserving low energy distributions

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• Saturation occurs at every energy
• Is this a good thing? I think so, as long as the
  linear region in each energy bin is sufficiently
  wide

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Analysis of

• Energy distribution of final state particles in
  jets
• Choose a ?R 0.5 cone around a quark to define a
  jet
• Determine energy fraction of jets carried by EM,
  Neutral and Hadrons
• Determine the relative distances between all
  pairs of charged, neutral particles in the cone
• Use two pions to study effective charged hadron
  energy subtraction
• Study of centroid finding algorithm

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Energy distribution in a jet
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Fraction Energy of Particles in Jets
Neutral Hadrons
Electromagnetic
Charged Hadrons
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DR Between All Particles in Jets
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Energy Flow Studies for p-

• Pions ?E p- ? 7.5 GeV chosen for study
• Studied the energy distribution of pions in jet
  events
• Find the centroid of the shower ( HCAL ) using
• Energy weighted method
• Hits weighted method
• Density weighted method
• Matched the extrapolated centroid with TPC last
  layer hit to get ?? and ?f distribution

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Determination of Calorimeter Centroid

• Identify layers with hits (at least 3 hits
  required)
• Fit a line through all layers (at least 2 layers
  with 3 or more hits required)
• Extrapolate the line to TPC last layer
• Compare ?tpc with ?hcal and ?tpc with ?hcal

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Methods for determination of centroid
Hits Weighted Method
Energy Weighted Method
Density Weighted Method
For all three methods
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?? - 7.5 GeV p-
Density Weighted Method
Energy Weighted Method
Hits Weighted Method
22
?? - 7.5 GeV p-
Density Weighted Method
Energy Weighted Method
Hits Weighted Method
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Conclusions

• GEM Analog and digital performance studies
  completed
• GEM Analog resolution a nit worse than TDR and
  other studies due to large Landau like
  fluctuation
• GEM Digital resolution comparable with TDR and
  other studies
• Threshold dependence in progress
• Translate these resolutions into jet energy
  resolution
• A energy flow algorithm study using single pion
  events began
• DR of single particles in typical jets
• ?? and ?? using 3 different methods
• Compared the three methods
• Durham jet algorithm is being implemented
• Resolving 2 pions as function of DR using Mokka
• Kaushik is working on his thesis that will
  contain both the studies
• A visiting professor and an undergraduate student
  will join this semester for EFA studies