A team of researchers from Chalmers participated in the SKA Data Challenge 2, which took place in 2021. The Swedish team FORSKA-Sweden took a second place in the challenge, very close to the winners, the MINERVA team (Paris Observatory). Both teams used a Machine Learning approach to find galaxies in the challenge data, showing the potential of such techniques. The FORSKA-Sweden team also received a Silver medal in the reproducibility awards for best practices in their software pipeline.

Participating in this challenge brought expertise to the Onsala Space Observatory through a collaboration with Fraunhofer-Chalmers Centre, demonstrating that an interdisciplinary team of computer scientists, software developers and astronomers working together is a good combination to exploit the scientific output of the huge datasets that SKA will deliver.

The SKAO Data Challenges are designed to prepare future users to efficiently handle SKAO data. This second data challenge was set up to identify neutral hydrogen from galaxies at the frequencies that SKA will observe in the future. For that purpose, SKAO prepared a simulated dataset 1TB in size in which they ingested millions of simulated galaxies as well as the telescope response.

You can read more about the SKA Data Challenge 2 in this Press Release from SKAO and in accompanying papers ( Håkansson et al. 2023; Hartley et al. 2023 ).