Difference between revisions of "LE algo"
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| − | Below: As above, for the interpolated data, but only events where a track can be fitted are selected. Tzero was obtained by fitting a straight line to the leading edge of the drift time histo and taking the value where it crosses the x-axis. First the drift-time histo was put into 4ns bins to unify any double-maxima in the histogram. (Events with ADC data going above pedestal mean + 5 sigma are selected. Events with 5 or more hits are selected. 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 3 sigma.) | + | Below: As above, for the interpolated data, but only events where a track can be fitted are selected. Tzero was obtained by fitting a straight line to the leading edge of the drift time histo (between the overall maximum and the minimum preceding it) and taking the value where it crosses the x-axis (this needs work). First the drift-time histo was put into 4ns bins to unify any double-maxima in the histogram. (Events with ADC data going above pedestal mean + 5 sigma are selected. Events with 5 or more hits are selected. 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 3 sigma.) |
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Revision as of 16:57, 18 May 2011
- Page still under edit, incomplete
Results using Gerard's leading edge algo to extract drift-time from CDC prototype cosmics data
- 50/50 mixed Ar, CO2
- Recalibrated MFCs
- Outer plenum added to CDC prototype to prevent leaks
- New modified HVB
- 2050V
- Modified preamp4 (terminating resistors removed)
- Prototype tilted at 45o to enclosing scintillators (which trigger daq)
The original algorithm is here LE algo It takes 50 samples from the ADC data, convolutes them with the filter which I think is the inverse of the filter which the fADC uses when it digitises its input, optionally interpolates 4 extra points between each sample, and returns the first value above a predefined threshold. There are a variety of implementations below.
Below: Events with ADC data going above pedestal mean + 5 pedestal sigma are selected. 50 samples starting 25 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 2 pedestal sigma. Pedestal mean is for 100 early samples in the event. Pedestal sigma is for 100 early samples in 100 events.
Left: drift-time with interpolation; Right: no interpolation
Below: 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after pedestal subtraction.
Below: Events with ADC data going above pedestal mean + 5 sigma are selected. Events with 5 or more hits are selected. 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 3 sigma. Left: drift-time with interpolation; Right: no interpolation
Below: As above, for the interpolated data, but only events where a track can be fitted are selected. Tzero was obtained by fitting a straight line to the leading edge of the drift time histo (between the overall maximum and the minimum preceding it) and taking the value where it crosses the x-axis (this needs work). First the drift-time histo was put into 4ns bins to unify any double-maxima in the histogram. (Events with ADC data going above pedestal mean + 5 sigma are selected. Events with 5 or more hits are selected. 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 3 sigma.)
Negative residuals come from a tzero that is too small (or drift time that is too large). 3 sigma is ~ 30 in ADC value, probably too late. Lowering the LE threshold makes it more likely to accept noise before the signal and so the # tracked events decreases slightly.
Below: as above, for LE threshold of 1 sigma. (Events with ADC data going above pedestal mean + 5 sigma are selected. Events with 5 or more hits are selected. 20 samples starting 10 samples before the threshold crossing are sent to the LE algo after subtracting mean pedestal. The threshold for the LE algo is 1 sigma.)
