Difference between revisions of "CDC algo tuning"

Revision as of 18:27, 4 December 2013

Using prototype data from CDC_50_50 (run 31924) with offline analysis

50/50 Ar/CO₂ and cosmics, 2100V, prototype horizontal

Original code, many samples upsampled

1. Event pedestal is mean of 100 samples ending at trigger time
2. Find hit threshold crossing
3. Step back <pedlead> points to find new pedestal
4. Search forward to find high threshold crossing
5. Search backward to find low threshold crossing
6. Project through both thresholds to find pedestal crossing time

All thresholds found using upsampled data, with interpolation

Thresholds 5-4-1 pedlead 16 tz 7 tfix 1000

Thresholds 5-4-2 pedlead 16 tz 7 tfix 1000

Thresholds 5-4-3 pedlead 16 tz 7 tfix 1000

All thresholds found using upsampled data, without interpolation at the high and low threshold xings

Thresholds 5-4-1 pedlead 16 tz 7 tfix 1000

Fewer samples upsampled

1. Event pedestal is mean of 100 samples ending at trigger time
2. Find hit threshold crossing
3. Upsample region around threshold crossing, with threshold crossing sample in set position
4. Step back <pedlead> points to find new pedestal
5. Search forward to find high threshold crossing
6. Search backward to find low threshold crossing
7. Project through both thresholds to find pedestal crossing time

High and low thresholds found using upsampled data, with interpolation

Thresholds 5-4-1 pedlead 16 tz 7 tfix 1000

Ideas

1. Check whether interpolating threshold xings makes any difference - no, not if extrapolating through thresholds to pedestal.
2. Use the 3rd sample (or mean of 3rd & 4th samples) before hit threshold as local pedestal
3. Try reverting to one threshold crossing instead of the extrapolation
4. Try something easier for event pedestal - mean of 4 samples immediately before trigger