International Conference on Machine Learning for Astrophysics - ML4Astro

Session

SKA and Precursors

1 Jun 2022, 11:30

Catania

Conveners

SKA and Precursors: Session 2

• Andrea Possenti (Istituto Nazionale di Astrofisica (INAF))

40. A machine learning classifier for LOFAR radio galaxy cross-matching techniques

Lara Alegre (Institute for Astronomy, University of Edinburgh)

01/06/2022, 11:30

Oral Presentation

New-generation radio telescopes like LOFAR are conducting extensive sky surveys, detecting tens of millions of radio sources. To maximise the scientific value of these surveys, radio source components must be properly associated into physical sources before being cross-matched with their optical/infrared counterparts. We use machine learning to identify those radio sources for which either...

39. Analysis of Instance Segmentation Networks for Dispersed FRB Searches

Anastasia Seifert (University of Malta)

01/06/2022, 11:50

Oral Presentation

Next generation telescopes such as the SKA will be collecting a substantial amount of radio data in future surveys. The number of Fast Radio Burst (FRB) events are expected to increase as a result of the SKA having a higher sensitivity and resolution; thus increasing the volume of data collected which will consequently need to be analyzed and processed. Therefore, the previous methods of FRB...

41. Deep learning 21cm light-cones in 3D

Caroline Heneka (UHH)

01/06/2022, 12:10

Oral Presentation

Interferometric measurements of the 21cm signal with the Square Kilometre Array are a prime example of the data-driven era in astronomy and astrophysics we are entering with current and upcoming experiments. To optimally learn the Universe from low to high redshift I advocate for the use of multiple lines (multi-line intensity mapping) and complementary galaxy survey data, as well as the...