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ATWD WF feature extraction

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

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  1. ATWD WF feature extraction Spencer Klein, Dmitry Chirkin, LBNL IceCube meeting, Uppsala, 2004

  2. 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

  3. 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

  4. 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

  5. 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

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