A study of errors in RHESSI clean maps by adding noise to the calibrated event list. Pascal Saint-Hilaire Space Sciences Laboratory, University of California,

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Presentation transcript:

A study of errors in RHESSI clean maps by adding noise to the calibrated event list. Pascal Saint-Hilaire Space Sciences Laboratory, University of California, Berkeley 9 th RHESSI Workshop Genoa, 2009/09/03

Method: Interrupt image processing right after calibrated event list has been calculated Interrupt image processing right after calibrated event list has been calculated For each bin, retrieve number of counts C, corrected for detector livetime For each bin, retrieve number of counts C, corrected for detector livetime Replace this number of counts C Replace this number of counts C with a Poisson-distributed value Go on with image processing… Used CLEAN with SCs 3-9, uniform weighting. Took flux insode 50% contours in chosen boxes

2002/02/20 11:06:00-11:06:34

/- 905 ph/s/cm 2 /keV 1 min, 5-6 keV

4s, 5-6 keV

4s, 9-10 keV

4s, keV

4s, keV

CLEAN (x10) vis_fwdfit

Conclusions / ToDo Good way to estimate photometric errors, but lengthy! Good way to estimate photometric errors, but lengthy! Above 1000 cts in image, error on flux of features about 20%. Above 1000 cts in image, error on flux of features about 20%. Some features not so reliable, even if image has 1000 counts Some features not so reliable, even if image has 1000 counts Should try same with other imaging algorithms (pixon, uv_smooth, mem_njit,…) Should try same with other imaging algorithms (pixon, uv_smooth, mem_njit,…) 50% contours  all flux in box 50% contours  all flux in box

2002/02/20 11:06:00-11:06:34