Speaker
Description
The Evolutionary Map of the Universe (EMU) survey is an ongoing large-scale radio continuum survey conducted by ASKAP, which will discover around 40 million radio sources. While conventional source-finding algorithms could handle ~90% of source cataloguing in EMU, there might be 4 million sources with well-extended and complex morphological structures awaited to be identified through visual inspection or reliable machine-learning methods. In this talk, I will introduce the Radio Galaxy Zoo: EMU (RGZ-EMU) citizen science project, explaining how the use of citizen science/machine learning helps to characterise the observed radio emission of these complex sources and associate them with belonging host galaxies we use multi-wavelength observations of the same sky area. Team efforts in outreach and education will also be mentioned.
| In-person or online? | in-person |
|---|---|
| keywords | AGN, machine learning, citizen science, cross-matching, source finding |
| Career level | ECR |
