Realising the LOFAR Two-Metre Sky Survey -- using the supercomputer JUWELS at the Forschungszentrum J\"ulich

TL;DR

This paper discusses how the LOFAR Two-Metre Sky Survey leverages the JUWELS supercomputer at Forschungszentrum Jülich to process vast radio astronomy data efficiently, enabling large-scale sky mapping at high resolution.

Contribution

It introduces a robust, automated system that processes LOFAR data on the JUWELS supercomputer, significantly advancing data handling for large radio surveys.

Findings

Processed over 500 LOFAR observations using the prefactor pipeline.

Reduced data size significantly through calibration and processing.

Enabled large-scale, high-resolution sky mapping.

Abstract

The new generation of high-resolution broad-band radio telescopes, like the Low Frequency Array (LOFAR), produces, depending on the level of compression, between 1 to 10 TB of data per hour after correlation. Such a large amount of scientific data demand powerful computing resources and efficient data handling strategies to be mastered. The LOFAR Two-metre Sky Survey (LoTSS) is a Key Science Project (KSP) of the LOFAR telescope. It aims to map the entire northern hemisphere at unprecedented sensitivity and resolution. The survey consist of 3 168 pointings, requiring about 30 PBytes of storage space. As a member of the German Long Wavelength Consortioum (GLOW) the Forschungszentrum J\"ulich (FSZ) stores in the Long Term Archive (LTA) about 50% of all LoTSS observations conducted to date. In collaboration with SURFsara in Amsterdam we developed service tools that enable the KSP to process LOFAR data stored in the J\"ulich LTA at the supercomputer JUWELS in an automated and robust fashion. Through our system more than 500 out of 800 existing LoTSS observations have already been processed with the prefactor pipeline. This pipeline calibrates the direction-independent instrumental and ionospheric effects and furthermore reduces the data size significantly. For continuum imaging, this processing pipeline is the standard pipeline that is executed before more advanced processing and image reconstruction methods are applied.