A study of errors in A study of errors in RHESSI clean maps by RHESSI clean maps by

adding noise to the adding noise to the calibrated event list.calibrated event list.

Pascal Saint-HilaireSpace Sciences Laboratory, University of California,

Berkeley

9th RHESSI WorkshopGenoa, 2009/09/03

Method:Method: Interrupt image processing right after Interrupt image processing right after

calibrated event list has been calculatedcalibrated event list has been calculated For each bin, retrieve number of counts For each bin, retrieve number of counts CC, ,

corrected for detector livetimecorrected for detector livetime Replace this number of counts Replace this number of counts CC 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

14070 +/- 905 ph/s/cm2/keV

1 min, 5-6 keV

4s, 5-6 keV

4s, 9-10 keV

4s, 17-18 keV

4s, 24-25 keV

CLEAN (x10)

vis_fwdfit

Conclusions / ToDoConclusions / ToDo

Good way to estimate photometric Good way to estimate photometric errors, but lengthy!errors, but lengthy!

Above 1000 cts in image, error on flux Above 1000 cts in image, error on flux of features about 20%.of features about 20%.

Some features not so reliable, even if Some features not so reliable, even if image has 1000 countsimage has 1000 counts

Should try same with other imaging Should try same with other imaging algorithms (pixon, uv_smooth, algorithms (pixon, uv_smooth, mem_njit,…)mem_njit,…)

50% contours 50% contours all flux in box all flux in box

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