Using Wavelet Transforms to Detect Dust in Cosmic Microwave Background Maps

Details Using Wavelet Transforms to Detect Dust in Cosmic Microwave Background Maps Using Wavelet Transforms to Detect Dust in Cosmic Microwave Background Maps

May 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008aas...212.2303r&link_type=abstract

American Astronomical Society, AAS Meeting #212, #23.03; Bulletin of the American Astronomical Society, Vol. 40, p.220

Statistics

Scientific paper

A major question regarding temperature fluctuations in the cosmic microwave background (CMB) is whether or not they obey Gaussian statistics (i.e., whether they contain any additional information beyond that contained in the power spectrum). Inflation predicts that the CMB is Gaussian; future experiments will test this prediction. Dust contamination will likely be a problem for these tests, and could bias the results, as dust is known to be highly non-Gaussian. We are developing statistical test to detect dust contamination.
It has previously been shown that wavelet transforms efficiently represent dust, so we compare the power of a variety of statistical tests to maps with and without wavelet transforms. Some statistics we have looked at are the skewness, linear correlations between a simulated map and a dust template, and a comparison of the mean-square signal in high-dust and low-dust regions. We have found that using a wavelet transform does not help detect dust for the skewness test, but it significantly increases the power of the mean-square test.
This research is supported by grants from the National Science Foundation and the Research Corporation.

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