Southern Site Data Analysis Status at CSU

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Southern SiteData Analysis Status at CSU
Pablo Bauleo
Physics Department Colorado State University Ft
Collins, CO 80523
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Outline

• Hybrid Trigger Efficiency
• In collaboration with Adrian Rovero (IAFE)
• Carmen-Miranda Signal Fluctuation
• Lateral Distribution Function

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Hybrid Trigger in a nutshell

• When a shower candidate is detected by the FD a
  T3 signal is sent to CDAS (including estimated
  core impact time and position)
• CDAS requests all the tanks to check if they have
  in their buffers a signal within the time window
  corresponding to the shower front crossing the
  particular detector (FD core impact time and
  position required)
• If any tank has a time coincidence signal, an
  Hybrid Trigger is produced.

Hybrid Trigger Efficiency, P. Bauleo and A. Rovero
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Hybrid Trigger Efficiency

• Objectives
• Measure FD/SD/Hybrid intrinsic trigger efficiency
• Improve trigger algorithms (if possible)
• Find out how many EAS were missed by SD array
• Trigger Efficiency depends on several parameters
  (E,q, etc) but we fold all of them into a global
  efficiency (for the time being) due to low
  statistics
• Guideline
• Using only the information of the FD (monocular
  reconstructed EAS ), look for those events
  falling inside the SD array boundaries.
• For that event subset, check the status of the
  closest tank to core impact position (? 5 minutes
  from FD GPS time)
• If hybrid ? Tank is running (double check)
• If not hybrid ? Tank might or might not be
  running

Hybrid Trigger Efficiency, P. Bauleo and A. Rovero
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Data Selection

• Cuts
• 9 ? Npix ? 45 ? reject noise and lighting
• Nice reconstructed events (Monocular)
• Energy between 1016 eV and 1022 eV
• Energy error ? 15
• Zenith angle error ? 15 ? Translates into a
  small error in core position
• Zenith angle ? 60
• 0.001 ? ChiSquare ? 10
• Closest tank ? 0.8 km from core ? events
  contained within array boundaries
• Out of 3625 FD-triggers, only 50 survived all
  the cuts.
• Too tough? Maybe, but we are just developing the
  criteria
• Note some files seems to be corrupted in both
  databases (FD SD)

Hybrid Trigger Efficiency, P. Bauleo and A. Rovero
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FD selected events and SD Status

• For these selected FD events, the status of the
  array (tanks up/down, etc) was surveyed for 10
  minutes (centered at the FD event time)
• Some of the FD-only events were detected when the
  whole array or the closest detector to the core
  were not running ? Good reason for not being
  hybrid

Hybrid Trigger Efficiency, P. Bauleo and A. Rovero
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(Current) Conclusion

• For the selected events (Emean 1 EeV and
  ?mean 300)
• 34 hybrid events (after cuts)
• 4 events were FD-only due to SD down
• 12 FD-only without a good reason (yet) not to
  be hybrid
• SD intrinsic trigger efficiency has to be folded
  into the analysis
• Note SD-ToT was implemented in mid march!!!
• Hybrid Trigger Efficiency 74
• These value depends on the cuts/criteria used
• Next steps
• Improve events selection criteria and/or run over
  the whole FD database
• Use more than the closest tank status for the
  analysis
• Look for SD-only events that should have been
  detected by the FD

Hybrid Trigger Efficiency, P. Bauleo and A. Rovero
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Carmen-Miranda

• Data Selection
• March-June 02 Run
• Multiplicity larger or equal to 4 (with CM)
• No lone tanks (accidental tank rejection)
• All trigger times compatible with shower front
  crossing the array
• Nevents 435

• Data Analysis
• Studied signal difference as function of C and M
  signal
• D (sSD/Signal) is plotted as function of C and
  M signal

Carmen-Miranda signal accuracy, P. Bauleo and J.
Harton
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Carmen-Miranda signal accuracy
Carmen-Miranda signal accuracy, P. Bauleo and J.
Harton
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Lateral Distribution Function(CSU-Karlshure-Leeds
-Torino- UNLP)

• Data Selection Criteria
• Looking for events highly symmetric with large
  multiplicity (i.e. the core position can be
  easily obtained because 3 or more stations have
  roughly the same signal)
• Work is being done to tune the criteria
  (CSU-Karlshure-UNLP)
• Redundant density approach
• For those events, the core position is found
  using only the redundant tanks, using a simple
  (assumed) power-law LDF
• As the event have a large multiplicity, the
  remaining stations give information in the real
  LDF
• To avoid the self-fullfilling prophesy (J.
  Linsley) work is being done to find out the
  bias of the real LDF due to the assumed
  power-law LDF (Leeds-Karlshure)

Lateral Distribution Function report, P. Bauleo
on behalf of LDF Task Group
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Peeping the results

• Well behaved
• Reduced dispersion

• Not so well behaved
• Larger dispersion

Lateral Distribution Function report, P. Bauleo
on behalf of LDF Task Group