Pablo

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Published on November 7, 2007

Author: Nastasia

Source: authorstream.com

Southern Site Data Analysis Status at CSU:  Southern Site Data Analysis Status at CSU Pablo Bauleo Physics Department Colorado State University Ft Collins, CO 80523 Outline:  Outline Hybrid Trigger Efficiency In collaboration with Adrian Rovero (IAFE) Carmen-Miranda Signal Fluctuation Lateral Distribution Function Hybrid Trigger in a nutshell:  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 Hybrid Trigger Efficiency:  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 Data Selection:  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 FD selected events and SD Status:  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 (Current) Conclusion:  (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 Carmen-Miranda :  Carmen-Miranda Data Selection March-June ’02 Run Multiplicity larger or equal to 4 (with C&M) 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 Carmen-Miranda signal accuracy:  Carmen-Miranda signal accuracy, P. Bauleo and J. Harton Carmen-Miranda signal accuracy Lateral Distribution Function (CSU-Karlshure-Leeds-Torino- UNLP):  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 “Peeping” the results:  “Peeping” the results Lateral Distribution Function report, P. Bauleo on behalf of LDF Task Group Well behaved Reduced dispersion Not so well behaved Larger dispersion

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