LOFAR is a low-frequency radio telescope composed of thousands of simple antennas distributed across Europe, with most located in the north of the Netherlands. By combining signals from these stations, LOFAR can in principle deliver extremely high-resolution images over large regions of the sky. Achieving this, however, is highly challenging: the telescope generates massive data volumes that require complex calibration and imaging algorithms. Without careful calibration, the resulting images remain severely blurred.

Another hurdle is the computational expense, as single observations can produce images exceeding 10 gigapixels. These challenges long prevented imaging at LOFAR’s full theoretical resolution. Recently, by developing new algorithms and exploiting SURF’s high-throughput processing platform Spider, operated by the Distributed Data Processing team, together with SURF’s AI expertise from the High-Performance Machine Learning team, we have overcome these barriers—producing the deepest, highest-resolution LOFAR images of the Universe to date.