Avoiding bias in reconstructing the largest observable scales from partial-sky data

Details Avoiding bias in reconstructing the largest observable scales from partial-sky data Avoiding bias in reconstructing the largest observable scales from partial-sky data

2011-07-27

arxiv.org/abs/1107.5466v2

Phys.Rev.D84:103002,2011

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

8 pages, 8 figures. v2: replaced with version accepted by PRD (minor amendments to text only)

Scientific paper

10.1103/PhysRevD.84.103002

Obscuration due to Galactic emission complicates the extraction of information from cosmological surveys, and requires some combination of the (typically imperfect) modeling and subtraction of foregrounds, or the removal of part of the sky. This particularly affects the extraction of information from the largest observable scales. Maximum-likelihood estimators for reconstructing the full-sky spherical harmonic coefficients from partial-sky maps have recently been shown to be susceptible to contamination from within the sky cut, arising due to the necessity to band-limit the data by smoothing prior to reconstruction. Using the WMAP 7-year data, we investigate modified implementations of such estimators which are robust to the leakage of contaminants from within masked regions. We provide a measure, based on the expected amplitude of residual foregrounds, for selecting the most appropriate estimator for the task at hand. We explain why the related quadratic maximum-likelihood estimator of the angular power spectrum does not suffer from smoothing-induced bias.

Affiliated with

Also associated with

No associations

Rating

Avoiding bias in reconstructing the largest observable scales from partial-sky data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Avoiding bias in reconstructing the largest observable scales from partial-sky data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Avoiding bias in reconstructing the largest observable scales from partial-sky data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-113275