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Foreground Contamination in Interferometric Measurements of the Redshifted 21 cm Power Spectrum

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 Added by Judd Bowman
 Publication date 2009
  fields Physics
and research's language is English




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Subtraction of astrophysical foreground contamination from dirty sky maps produced by simulated measurements of the Murchison Widefield Array (MWA) has been performed by fitting a 3rd-order polynomial along the spectral dimension of each pixel in the data cubes. The simulations are the first to include the unavoidable instrumental effects of the frequency-dependent primary antenna beams and synthesized array beams. They recover the one-dimensional spherically-binned input redshifted 21 cm power spectrum to within approximately 1% over the scales probed most sensitively by the MWA (0.01 < k < 1 Mpc^-1) and demonstrate that realistic instrumental effects will not mask the EoR signal. We find that the weighting function used to produce the dirty sky maps from the gridded visibility measurements is important to the success of the technique. Uniform weighting of the visibility measurements produces the best results, whereas natural weighting significantly worsens the foreground subtraction by coupling structure in the density of the visibility measurements to spectral structure in the dirty sky map data cube. The extremely dense uv-coverage of the MWA was found to be advantageous for this technique and produced very good results on scales corresponding to |u| < 500 wavelengths in the uv-plane without any selective editing of the uv-coverage.



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We analyse the accuracy of radio interferometric gridding of visibilities with the aim to quantify the Epoch of Reionization (EoR) 21-cm power spectrum bias caused by gridding, ultimately to determine the suitability of different imaging algorithms and gridding settings for 21-cm power spectrum analysis. We simulate realistic LOFAR data, and construct power spectra with convolutional gridding and w-stacking, w-projection, image domain gridding and without w-correction. These are compared against directly Fourier transformed data. The influence of oversampling, kernel size, w-quantization, kernel windowing function and image padding are quantified. The gridding excess power is measured with a foreground subtraction strategy, for which foregrounds have been subtracted using Gaussian progress regression, as well as with a foreground avoidance strategy. Constructing a power spectrum that has a bias significantly lower compared to the expected EoR signals is possible with the tested methods, but requires a kernel oversampling factor > 4000 and, when using w-correction, > 500 w-quantization levels. These values are higher than typical values used for imaging, but are computationally feasible. The kernel size and padding factor parameters are less crucial. Among the tested methods, image domain gridding shows the highest accuracy with the lowest imaging time. LOFAR 21-cm power spectrum results are not affected by gridding. Image domain gridding is overall the most suitable algorithm for 21-cm EoR experiments, including for future SKA EoR analyses. Nevertheless, convolutional gridding with tuned parameters results in sufficient accuracy. This holds also for w-stacking for wide-field imaging. The w-projection algorithm is less suitable because of the kernel oversampling requirements, and a faceting approach is unsuitable due to the resulting spatial discontinuities.
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Contamination from instrumental effects interacting with bright astrophysical sources is the primary impediment to measuring Epoch of Reionization and BAO 21 cm power spectra---an effect called mode-mixing. In this paper we identify four fundamental power spectrum shapes produced by mode-mixing that will affect all upcoming observations. We are able, for the first time, to explain the wedge-like structure seen in advanced simulations and to forecast the shape of an EoR window that is mostly free of contamination. Understanding the origins of these contaminations also enables us to identify calibration and foreground subtraction errors below the imaging limit, providing a powerful new tool for precision observations.
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