We develop two methods for estimating the power spectrum, C_l, of the cosmic microwave background (CMB) from data and apply them to the COBE/DMR and Saskatoon datasets. One method involves a direct evaluation of the likelihood function, and the other is an estimator that is a minimum-variance weighted quadratic function of the data. Applied iteratively, the quadratic estimator is not distinct from likelihood analysis, but is rather a rapid means of finding the power spectrum that maximizes the likelihood function. Our results bear this out: direct evaluation and quadratic estimation converge to the same C_ls. The quadratic estimator can also be used to directly determine cosmological parameters and their uncertainties. While the two methods both require O(N^3) operations, the quadratic is much faster, and both are applicable to datasets with arbitrary chopping patterns and noise correlations. We also discuss approximations that may reduce it to O(N^2) thus making it practical for forthcoming megapixel datasets.
We present full sky microwave maps in five frequency bands (23 to 94 GHz) from the WMAP first year sky survey. Calibration errors are less than 0.5% and the low systematic error...
We present measurements of galaxy clustering from the Baryon Oscillation\nSpectroscopic Survey (BOSS), which is part of the Sloan Digital Sky Survey III\n(SDSS-III). These use t...
Gravitational lensing due to the large-scale distribution of matter in the cosmos distorts the primordial cosmic microwave background (CMB) and thereby induces new, small-scale ...
This paper is concerned with the problem of estimating the mean and variance of normal populations from singly and doubly truncated samples having known truncation points. Maxim...
We examine the possibility that a significant component of the energy density of the universe has an equation-of-state different from that of matter, radiation or cosmological c...
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