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Register a new userApplication of a Bayesian Method to Absorption Spectral-Line Finding in Simulated ASKAP Data
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J. R. Allison
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The large spectral bandwidth and wide field of view of the Australian SKA Pathfinder radio telescope will open up a completely new parameter space for large extragalactic HI surveys. Here we focus on identifying and parametrising HI absorption lines which occur in the line of sight towards strong radio continuum sources. We have developed a method for simultaneously finding and fitting HI absorption lines in radio data by using multi-nested sampling, a Bayesian Monte Carlo algorithm. The method is tested on a simulated ASKAP data cube, and is shown to be reliable at detecting absorption lines in low signal-to-noise data without the need to smooth or alter the data. Estimation of the local Bayesian evidence statistic provides a quantitative criterion for assigning significance to a detection and selecting between competing analytical line-profile models.
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The Evolutionary Map of the Universe (EMU) is a proposed radio continuum survey of the Southern Hemisphere up to declination +30 deg., with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU will use an automated source identification and measurement approach that is demonstrably optimal, to maximise the reliability, utility and robustness of the resulting radio source catalogues. As part of the process of achieving this aim, a Data Challenge has been conducted, providing international teams the opportunity to test a variety of source finders on a set of simulated images. The aim is to quantify the accuracy of existing automated source finding and measurement approaches, and to identify potential limitations. The Challenge attracted nine independent teams, who tested eleven different source finding tools. In addition, the Challenge initiators also tested the current ASKAPsoft source-finding tool to establish how it could benefit from incorporating successful features of the other tools. Here we present the results of the Data Challenge, identifying the successes and limitations for this broad variety of the current generation of radio source finding tools. As expected, most finders demonstrate completeness levels close to 100% at 10sigma dropping to levels around 10% by 5sigma. The reliability is typically close to 100% at 10sigma, with performance to lower sensitivities varying greatly between finders. All finders demonstrate the usual trade-off between completeness and reliability, whereby maintaining a high completeness at low signal-to-noise comes at the expense of reduced reliability, and vice-versa. We conclude with a series of recommendations for improving the performance of the ASKAPsoft source-finding tool.
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