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spacetelescope / jwst

Python library for science observations from the James Webb Space Telescope
https://jwst-pipeline.readthedocs.io/en/latest/
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CR showers code excessive flagging in MRS bright sources #8616

Open stscijgbot-jp opened 5 days ago

stscijgbot-jp commented 5 days ago

Issue JP-3677 was created on JIRA by David Law:

Filing a ticket to track this as additional examples have arisen in the community.

The MIRI CR showers routine can sometime flag genuine source pixels as showers for very bright sources.  Previously this was noted primarily for observations of Jupiter and Saturn, which have ultra-bright continua, and complex spectra that cause saturation in multiple places.  This has now been seen in galaxy data though, flagging large sections of continuum emission around bright spectral lines.

As an example, see jw01701012001_02105_00001_mirifulong_uncal

The figure attached shows the region around a bright Ch3 emission line processed with the default B11.0 pipeline on the left, and with the showers routine enabled on the right.  Perhaps it's worth capping how bright showers can be?  Unlike snowballs than can range in magnitude, showers are all low-level blotches that are never (as far as I'm aware) in excess of a few DN/s.

m-samland commented 20 hours ago

Could you elaborated @drlaw1558? I think I might have a dataset in which the top of emission might be cut off because of such an issue. Is this happening due to parameters set in the jump detection step or one of the other correction steps (pixel replace / spec3 outlier rejection)?

drlaw1558 commented 19 hours ago

@m-samland : In the case listed here the issue is with the shower-correction routine in the jump step. When some pixels start saturating the shower flagging can expand the size of the flagged regions too much. Note that the shower-correction is turned off by default in the pipeline at the moment for exactly this reason, so unless you're turning on the shower corrections in your own reprocessing this shouldn't currently affect you.

I'd suggest filing a helpdesk ticket for your dataset (if you haven't already) and we can try to see what's going on there.