SDC2: analysis and results

SKA Science Data Challenge 2: analysis and results

Over 100 participants worked to find and characterise 233,245 neutral hydrogen (HI) sources in a simulated data product representing a 2000-hour SKA-Mid spectral line observation from redshifts 0.25 to 0.5.

IRIS and seven other international supercomputing facilities provided dedicated computing resources.

‘Reproducibility awards’ were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy – which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance – underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets.