Nonparametric Inference for the Cosmic Microwave Background

Details Nonparametric Inference for the Cosmic Microwave Background Nonparametric Inference for the Cosmic Microwave Background

2004-10-06

arxiv.org/abs/astro-ph/0410140v1

Astronomy and Astrophysics

Astrophysics

Invited review for "Statistical Science". Accepted for publication in Feburary 2004 journal

Scientific paper

The Cosmic Microwave Background (CMB), which permeates the entire Universe, is the radiation left over from just 380,000 years after the Big Bang. On very large scales, the CMB radiation field is smooth and isotropic, but the existence of structure in the Universe - stars, galaxies, clusters of galaxies - suggests that the field should fluctuate on smaller scales. Recent observations, from the Cosmic Microwave Background Explorer to the Wilkinson Microwave Anisotropy Project, have strikingly confirmed this prediction. CMB fluctuations provide clues to the Universe's structure and composition shortly after the Big Bang that are critical for testing cosmological models. For example, CMB data can be used to determine what portion of the Universe is composed of ordinary matter versus the mysterious dark matter and dark energy. To this end, cosmologists usually summarize the fluctuations by the power spectrum, which gives the variance as a function of angular frequency. The spectrum's shape, and in particular the location and height of its peaks, relates directly to the parameters in the cosmological models. Thus, a critical statistical question is how accurately can these peaks be estimated. We use recently developed techniques to construct a nonparametric confidence set for the unknown CMB spectrum. Our estimated spectrum, based on minimal assumptions, closely matches the model-based estimates used by cosmologists, but we can make a wide range of additional inferences. We apply these techniques to test various models and to extract confidence intervals on cosmological parameters of interest. Our analysis shows that, even without parametric assumptions, the first peak is resolved accurately with current data but that the second and third peaks are not.

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