I had a fun conversation today with Fiona McCarthy (Flatiron) and Colin Hill (Columbia) about combining CMB maps that have been contaminated (by God) with foregrounds. The issue is that any machine-learning method for finding combination weights will deliver weights that are covariant with the true CMB signal, and thus bias the results importantly. We figured out that there are linear combinations of the maps that will have (by design) zero CMB signal in them! If we train our machine-learning method using those, it can't be sensitive to the CMB signal itself? Will it work? We'll see.
Tracy Chen and I used no-CMB linear combinations
ReplyDeleteto search for point sources.
@ARTICLE{2009ApJ...694..222C,
author = {{Chen}, X. and {Wright}, E.~L.},
title = "{Extragalactic Point Source Search in Five-Year WMAP 41, 61, and 94 Ghz Maps}",
journal = {\apj},
keywords = {catalogs, cosmic microwave background, cosmology: observations, methods: data analysis, Astrophysics},
year = 2009,
month = mar,
volume = {694},
number = {1},
pages = {222-234},
doi = {10.1088/0004-637X/694/1/222},
archivePrefix = {arXiv},
eprint = {0809.4025},
primaryClass = {astro-ph},
adsurl = {https://ui.adsabs.harvard.edu/abs/2009ApJ...694..222C},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}