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

TL;DR

This paper details software enhancements for the VLA Low-frequency Sky Survey, significantly improving image quality, source catalog completeness, and ionospheric correction accuracy through advanced algorithms and data processing techniques.

Contribution

Introduction of novel algorithms and software improvements in Obit for better data reduction and analysis of VLSS, enabling more accurate imaging and source cataloging.

Findings

50% reduction in clean bias

Number of sources increased by 35% to 95,000

Largest angular size imaged roughly doubled

Abstract

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 The improved reduction techniques led to substantial improvements including images of six previously unpublished fields (1% of the survey area) and reducing the clean bias by 50%.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.