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VLSS Redux: Software Improvements applied to the Very Large Array Low-frequency Sky Survey

We present details of improvements to data processing and analysis which were recently used for a re-reduction of the Very Large Array (VLA) Low-frequency Sky Survey (VLSS) data. Algorithms described are implemented in the data-reduction package Obit, and include smart-windowing to reduce clean bias, improved automatic radio frequency interference removal, improved bright-source peeling, and higher-order Zernike fits to model the ionospheric phase contributions. An additional, but less technical improvement was using the original VLSS catalog as a same-frequency/same-resolution reference for calculating ionospheric corrections, allowing more accuracy and a higher percentage of data for which solutions are found. We also discuss new algorithms for extracting a source catalog and analyzing ionospheric fluctuations present in the data. The improved reduction techniques led to substantial improvements including images of six previously unpublished fields (1% of the survey area) and reducing the clean bias by 50%. The largest angular size imaged has been roughly doubled, and the number of cataloged sources is increased by 35% to 95,000.

preprint2012arXivOpen access
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