4. Our Problem
There are ~10,000 archival solar system
images observed with HST's WFPC2.
Their current science products are not
optimized for moving targets.
We don't have a good catalog of what's in
these images.
5. Our Project
Create the high-quality science images
optimized for moving targets from every
WFPC2 solar system image.
Create a catalog of every object in every
WFPC2 solar system image.
6. Our Team
Max Mutchler (STScI) - P.I.
Dr. Susana Deusta (STScI)
Dr. Alberto Conti (STScI)
Alex Viana (STScI)
Dr. Mike Wong (Berkeley/University of
Michigan)
Dr. Pamela Gay (CosmoQuest, SIUE)
+ CosmoQuest Team
14. Hubble’s
Wide Field 2 WFPC2:
(WF2) both the camera and it’s
Planetary Camera archival images are
kinda weird
(PC1)
Archival mosaics
are drizzled to WF pixel
scale -- which means PC
pixels are binned by 2X
No rejection of cosmic
Wide Field 3 rays or detector artifacts
(WF3) Wide Field 4 -- or worse, bad
rejections!
(WF4)
Also -- what is on the WF
chips? How many of the
WF chips have never
been inspected by
anyone?
*
21. Our science-ready images are mosaics which are clean, resampled, distortion-free,
and include cataloged secondary objects and features, with planetary parameters
embedded in their headers
*
22. Our science-ready images are mosaics which are clean, resampled, distortion-free,
and include cataloged secondary objects and features, with planetary parameters
embedded in their headers
*
23. Our science-ready images are mosaics which are clean, resampled, distortion-free,
and include cataloged secondary objects and features, with planetary parameters
embedded in their headers
*
24. The standard calibration pipelines are not optimized for moving targets
Single-image
cosmic ray rejection:
requires visual verification,
iteration, and masking
*
25. The standard calibration pipelines are not optimized for moving targets
Single-image
cosmic ray rejection:
requires visual verification,
iteration, and masking
*
29. In addition to providing finder charts for each observation, we’d like to actually catalog
the contents of each image -- what is actually detected (and what is the data quality)?
*
34. For Every Image ...
1. Run CR rejection
2. Run astrodrizzle (x2)
3. Create PNG (x2+)
4. Get and convert metadata
5. Talk to JPL Horizons via telnet
6. Convert coordinates and find delta in pixels
7. See if "pixels" fall on the image
8. Save all the relevant information to a
database
2,200 lines of pure Python
36. Some Challenges
10k+ files --> 100k+ files
How do you know what version of your code
generated what files?
How do you know you code is working?
How do you keep track of every moon in 80k
different images?
39. Acknowledgements
Thanks to the Marietta College Department of
Physics for inviting me.
Thanks Max Mutchler and Dr. Pamela Gay for
their slides.
This work is funded by STScI Hubble Cycle 18
Legacy Archival Research proposal 12142