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University of Richmond

Cosmology observations

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Full-Text Articles in Physics

Systematic Effects In Interferometric Observations Of The Cosmic Microwave Background Polarization, Ata Karakci, Le Zhang, P. M. Sutter, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt Jul 2013

Systematic Effects In Interferometric Observations Of The Cosmic Microwave Background Polarization, Ata Karakci, Le Zhang, P. M. Sutter, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt

Physics Faculty Publications

The detection of the primordial B-mode spectrum of the polarized cosmic microwave background (CMB) signal may provide a probe of inflation. However, observation of such a faint signal requires excellent control of systematic errors. Interferometry proves to be a promising approach for overcoming such a challenge. In this paper we present a complete simulation pipeline of interferometric observations of CMB polarization, including systematic errors. We employ two different methods for obtaining the power spectra from mock data produced by simulated observations: the maximum likelihood method and the method of Gibbs sampling. We show that the results from both methods …


Maximum Likelihood Analysis Of Systematic Errors In Interferometric Observations Of The Cosmic Microwave Background, Le Zhang, Ata Karakci, Paul M. Sutter, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt Jun 2013

Maximum Likelihood Analysis Of Systematic Errors In Interferometric Observations Of The Cosmic Microwave Background, Le Zhang, Ata Karakci, Paul M. Sutter, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt

Physics Faculty Publications

We investigate the impact of instrumental systematic errors in interferometric measurements of the cosmic microwave background (CMB) temperature and polarization power spectra. We simulate interferometric CMB observations to generate mock visibilities and estimate power spectra using the statistically optimal maximum likelihood technique. We define a quadratic error measure to determine allowable levels of systematic error that does not induce power spectrum errors beyond a given tolerance. As an example, in this study we focus on differential pointing errors. The effects of other systematics can be simulated by this pipeline in a straightforward manner. We find that, in order to accurately …