Crowded Field Photometry and Moving Object Detection with Optimal Image Subtraction

Details Crowded Field Photometry and Moving Object Detection with Optimal Image Subtraction Crowded Field Photometry and Moving Object Detection with Optimal Image Subtraction

May 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21641506l&link_type=abstract

American Astronomical Society, AAS Meeting #216, #415.06; Bulletin of the American Astronomical Society, Vol. 41, p.825

Astronomy and Astrophysics

Astronomy

Scientific paper

High precision photometry and moving object detection are essential in the study of Pluto and the Kuiper Belt. In particular, the New Horizons mission would benefit from an accurate and fast method of performing image subtraction to locate faint Kuiper Belt Objects (KBO) among large data sets.
The optimal image subtraction (OIS) algorithm was optimized for IDL to decrease execution time by a factor of about 140 from a previous implementation (Miller 2008, PASP, 120, 449). In addition, a powerful image transformation and interpolation routine was written to provide OIS with well-aligned input images using astrometric fit data.
The first half of this project is complete including the code optimization and the alignment routine. The second half of the project is focused on using these tools to search a 5 x 10 degree search area to find KBOs for possible targets for the New Horizons mission. We will present examples of how these tools work and along with resulting Pluto photometry and KBO target lists. The optimized OIS and transformation routines are available in Marc Buie's IDL library at http://www.boulder.swri.edu/ buie/idl/ as ois.pro and dewarp.pro.
This project was conducted for Harvey Mudd College's Clinic Program with financial support from the NASA Planetary Astronomy Program grant number NNX09AB43G.

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