WARP: fitting gamma signals

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Presentation transcript:

WARP: fitting gamma signals Graphic and Minuit-based program able to reconstruct time and amplitude of two signals produced by gamma events in WARP detector. Readout of input data file (binary structured) (Riccardo). Graphics (Andrea). Minuit strategy (Rinaldo): catch the highest signal (usually the secondary) fix highest signal parameters and look for smaller signal (usually the primary). free all parameters and try overall fit. Compute fit amplitudes and time.

Signal-shape fit by an empirical function (two peaks only) 9 free parameters

Definitions Secondary amplitude Base line Primary amplitude

Good event first step

Good event last step c2 = 0.72

Bad event first step

Bad event last step Rejected by c2 = 20.3

Bad event first step

Bad event last step accepted by c2 = 2.1 This topology is the only contribution to the contamination of the sample. A strategy could be defined to cut this kind of events.

Normalized c2 distribution

Efficiency and contamination Very preliminary Total efficiency in reconstructing good events: . . . . . . . . . . . . . . . . . . 85 % Total efficiency in rejecting bad events: . . . . . . . . . . . . . . . . . . . 88 % It results a 12 % contamination of bad events in the accepted sample

Time performances The production rate of DARK program is about: 5.0 event / minute (could be improved) 7200 events / day

Preliminary results 50000 triggers

50000 triggers c2 cut

Secondary spectrum - data 4000

Comparison manual vs fit amplitudes

Comparison bet. fit and manual secondary spectrum

Conclusion Improvements : Measure with higher accuracy (statistics) efficiency and contamination, Improve the speed of the program Study a strategy for “neutron” signals.