Bursts from Space: MeerKAT - the first citizen science project dedicated to commensal radio transients

The newest generation of radio telescopes is able to survey large areas with high sensitivity and cadence, producing data volumes that require new methods to better understand the transient sky. Here, we describe the results from the first citizen science project dedicated to commensal radio transients, using data from the MeerKAT telescope with weekly cadence. Bursts from Space: MeerKAT was launched late in 2021 and received similar to 89 000 classifications from over 1000 volunteers in 3 months. Our volunteers discovered 142 new variable sources which, along with the known transients in our fields, allowed us to estimate that at least 2.1 per cent of radio sources are varying at 1.28 GHz at the sampled cadence and sensitivity, in line with previous work. We provide the full catalogue of these sources, the largest of candidate radio variables to date. Transient sources found with archival counterparts include a pulsar (B1845-01) and an OH maser star (OH 30.1-0.7), in addition to the recovery of known stellar flares and X-ray binary jets in our observations. Data from the MeerLICHT optical telescope, along with estimates of long time-scale variability induced by scintillation, imply that the majority of the new variables are active galactic nuclei. This tells us that citizen scientists can discover phenomena varying on time-scales from weeks to several years. The success both in terms of volunteer engagement and scientific merit warrants the continued development of the project, while we use the classifications from volunteers to develop machine learning techniques for finding transients.

Automated summary

The newest generation of radio telescopes can survey large areas with high sensitivity and cadence, producing data volumes that require new methods to understand the transient sky. The first citizen science project dedicated to commensal radio transients, using data from the MeerKAT telescope, discovered 142 new variable sources and estimated that at least 2.1% of radio sources are varying at the sampled cadence and sensitivity. The success of volunteer engagement and scientific merit warrants the continued development of the project and the use of volunteer classifications to develop machine learning techniques for finding transients.