Understanding Glitches in PACS Photometer Data: Mitigation and Analysis Techniques

1. Glitches in PACS photometer BA & BA NHSC DP workshop

2. What are glitches? • Anomalous signal readouts caused by: • Charged particle hits to bolometer pixel. • “standard” glitches • Charged particle hits to electronics. • “dropouts” • Erratic behavior in the readout electronics. NHSC DP workshop

3. “Standard” Glitches • Thanks to the small cross section of the bolometer, the cosmic ray rate in very low. • <10 hits / array / readout [<0.5%] • Most are short-lived (1-2 readouts) • Can be both positive or negative (wall) • Mitigation • MMT deglitcher module • scan-map • Sigma clipping • point-source NHSC DP workshop

4. The MMT deglitcher • Based on ISOCAM wavelet source finder by Stark (1998, PASP, 110, 193) • Segregates the various temporal scales in the time streams in wavelet space. • A range of wavelet scales coupled with significance threshold define “glitch” in the data. NHSC DP workshop

5. Relevant MMT deglitcher parameters • scales • Number of wavelet scales. This should reflect the maximum number of affected pixels. • nsigma • The significance threshold in wavelet space. Values above nsigma*RMS are considered glitches. Where RMS is measured per wavelet scale. • Other parameters determine the properties of how MMT scales are calculated. NHSC DP workshop

6. MMT usage • The default values of the parameters do not provide a good default for all scientific cases. • Usually requires “tuning” for optimal results. • The 'scales' parameter is the most relevant for a good performance of the method. • scales=3 provides the best result for scan-maps at 20”/s scan speed • Scale=1 at high speed (parallel mode) • By default MMT deglitchers replace glitch with an interpolated value in dp.pacs 2.0, feature removed in dp.pacs 3.0 • This feature can be turned to ‘mask’ only, • maskOnly=True NHSC DP workshop

7. Bolometer behaves fortunately much better in space than in these radiation tests ! An example of MMT deglitching at work. Blue points show glitches in both signal space and corresponding wavelet space. NHSC DP workshop

8. Sigma Clipping • MMT deglitching is not a good choice for chopped observation. • chopper plateaus are incorrectly identified as glitches. • For point source (chopped) AOT observations. • Simple sigma clipping per chopper plateau per dither position. NHSC DP workshop

9. Signal steps • Discontinuous signal “jumps” • Much rarer • Likely, charged particle hit causes electronic offsets to “jump” • Even rarer: a full matrix upset • Mitigation: • With high pass filtering, only a few readouts near the discontinuity are affected. • Show up as anomalies in final maps. • Mask manually. NHSC DP workshop

10. DC offsets cases Line dropout Line up NHSC DP workshop

11. Erratic readouts • Signal is row 11 sometimes appears abnormal for a few readouts • Signal fluctuates between two values. • Causes not understood. • Mitigation: • Examine row 11 • Examine time-streams with mask viewer • Mask manually, as needed. NHSC DP workshop

12. 2nd level deglitching • HIPE also provides an alternative sigma-clip based de-glitcher. • it finds, for each pixel of the map, the list of all cube pixels that contribute to it and performs sigma clipping on this list to identify outliers. • However, • Current implementation is extremely memory intensive and slow • The data and projected cubes must be kept in memory

13. 2nd level deglitching • Do a sky projection without creating a map • photProject(frames, deglitch = True) • Perform sigma clipping on projected values • index = photProject.getValue("index") • from herschel.pacs.spg import IIndLevelDeglitchTask • from herschel.ia.numeric.toolbox.basic import Sigclip • deg = IIndLevelDeglitchTask() • s = Sigclip(10,10, outliers = "both") • img = deg(index, frames, mask=True, map=True, algo=s)