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ATWD WF feature extraction. Spencer Klein, Dmitry Chirkin, LBNL. IceCube meeting, Uppsala, 2004. Common waveform features. “zero” waveform similar shape (unless saturated) same (close) width. The question is: what is the time what is the charge
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ATWD WF feature extraction Spencer Klein, Dmitry Chirkin, LBNL IceCube meeting, Uppsala, 2004
Common waveform features • “zero” waveform • similar shape • (unless saturated) • same (close) width • The question is: • what is the time • what is the charge • This is needed for all photoelectrons in the waveform
Simple algorithm • find the minimum value • find the maximum value • use the 9 bins surrounding the maximum value: • subtract the minimum value • fit the gaussian, or: • using the values of the waveform as probabilities: • find the average • find the RMS • assign the average as timestamp • assign the sum over bin values • (or maximum*RMS) as charge
Future improvements • zero waveform precise measurement and subtraction • iterative gaussian fitting • or use the integrated (summed over bins) waveform and fit to it the sum of the erf functions • replace the gaussian model with more realistic one, which describes effects of the PMT signal processing
Conclusions • A simple 1pe gaussian fits were implemented and used in the analysis of the dark freezer lab DOMs • There is room for improvement: • more precise non-gaussian model, taking into account shaping by electronics • precise zero-waveform measurement and subtraction • multiple-hit waveform discovery and feature extraction • The simple algorithm will be implemented into the I3 module in the near future