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The ASKAP/EMU Source Finding Data Challenge

  • A. M. Hopkins (a1), M. T. Whiting (a2), N. Seymour (a3), K. E. Chow (a2), R. P. Norris (a2), L. Bonavera (a4), R. Breton (a5), D. Carbone (a6), C. Ferrari (a7), T. M. O. Franzen (a3), H. Garsden (a8), J. González-Nuevo (a4) (a9), C. A. Hales (a10) (a11), P. J. Hancock (a3) (a12) (a13), G. Heald (a14) (a15), D. Herranz (a4), M. Huynh (a16), R. J. Jurek (a2), M. López-Caniego (a4) (a17), M. Massardi (a18), N. Mohan (a19), S. Molinari (a20), E. Orrù (a14), R. Paladino (a18) (a21), M. Pestalozzi (a20), R. Pizzo (a14), D. Rafferty (a22), H. J. A. Röttgering (a23), L. Rudnick (a24), E. Schisano (a20), A. Shulevski (a14) (a15), J. Swinbank (a6) (a25), R. Taylor (a26) (a27) and A. J. van der Horst (a6) (a28)...

Abstract

The Evolutionary Map of the Universe (EMU) is a proposed radio continuum survey of the Southern Hemisphere up to declination + 30°, 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 and robustness of the resulting radio source catalogues. As a step toward this goal we conducted a “Data Challenge” to test a variety of source finders on simulated images. The aim is to quantify the accuracy and limitations of existing automated source finding and measurement approaches. 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. As expected, most finders show completeness around 100% at ≈ 10σ dropping to about 10% by ≈ 5σ. Reliability is typically close to 100% at ≈ 10σ, with performance to lower sensitivities varying between finders. All finders show the expected trade-off, where a high completeness at low signal-to-noise gives a corresponding reduction in 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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References

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