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Full-Text Articles in Physical Sciences and Mathematics
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
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 …
Bayesian Inference Of Polarized Cosmic Microwave Background Power Spectra From Interferometric Data, Ata Karakci, P. M. Sutter, Le Zhang, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt
Bayesian Inference Of Polarized Cosmic Microwave Background Power Spectra From Interferometric Data, Ata Karakci, P. M. Sutter, Le Zhang, Emory F. Bunn, Andrei Korotkov, Peter Timbie, Gregory S. Tucker, Benjamin D. Wandelt
Physics Faculty Publications
Detection of B-mode polarization of the cosmic microwave background (CMB) radiation is one of the frontiers of observational cosmology. Because they are an order of magnitude fainter than E-modes, it is quite a challenge to detect B-modes. Having more manageable systematics, interferometers prove to have a substantial advantage over imagers in detecting such faint signals. Here, we present a method for Bayesian inference of power spectra and signal reconstruction from interferometric data of the CMB polarization signal by using the technique of Gibbs sampling. We demonstrate the validity of the method in the flat-sky approximation for a simulation of an …
The Efficacy Of Galaxy Shape Parameters In Photometric Redshift Estimation: A Neural Network Approach, Jack Singal, M. Shmakova, B. Gerke, R. L. Griffith, J. Lotz
The Efficacy Of Galaxy Shape Parameters In Photometric Redshift Estimation: A Neural Network Approach, Jack Singal, M. Shmakova, B. Gerke, R. L. Griffith, J. Lotz
Physics Faculty Publications
We present a determination of the effects of including galaxy morphological parameters in photometric redshift estimation with an artificial neural network method. Neural networks, which recognize patterns in the information content of data in an unbiased way, can be a useful estimator of the additional information contained in extra parameters, such as those describing morphology, if the input data are treated on an equal footing. We use imaging and five band photometric magnitudes from the All-wavelength Extended Groth Strip International Survey. It is shown that certain principal components of the morphology information are correlated with galaxy type. However, we find …