Flavors of Coadds as discussed at Perfect Pixels, Accurate - PowerPoint PPT Presentation

Flavors of Coadds as discussed at Perfect Pixels, Accurate Astrophysics, Correct Cosmology as remembered/reconstructed by Jim Bosch

Some Definitions Direct Coadd: just combine per-epoch images with no modification to their PSFs ● ● combine per-epoch PSFs the same way to compute effective coadd PSF (requires "combine" to be strictly linear - no clipping or medians). PSF-Matched Coadd: convolve per-epoch images to a target PSF ● combination can use outlier rejection ● have to drop input images with PSFs [significantly] larger than target PSF. ●

Some Definitions Kaiser Coadd: ● formally optimal coadd: a sufficient statistic for the set of single-epoch images, assuming they only contain static sources. an old idea that still isn't widely known, and has been rediscovered a few times ● For more information see: ● Zackay & Ofek (2017) ○ Many more slides from me. ○ A sparse-matrix version (and generalization) from David Kirkby. ○

Comparing Flavors of Coadds

The Bottom Line, for LSST Direct coadds would probably be fine (Sheldon & Armstrong, in prep): difference in S/N from multi-epoch fitting is very small for realistic seeing distributions ● ● noise correlations can be propagated via Monte Carlo (possibly even just one sample) Kaiser coadds are even better - transforms slight concerns into non-concerns. The big open question is edges; do we: Also make per-object coadds (from scratch) for measurement? ● Make multiple coadds in each predefined cells and stitch them together? ● How do small-cell coadds interact with blends?