a study of errors in rhessi clean maps by adding noise to the calibrated event list. pascal...
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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
2002/02/20 11:06:00-11:06:34