Abstract

In this paper we discuss our efforts in ``unlocking'' the Long Term Archive (LTA) of the LOFAR radio telescope using the software ecosystem developed in the PROCESS project. The LTA is a large (>50 PB) archive that expands with about 7 PB per year by the ingestion of new observations. It consists of coarsely calibrated ``visibilities'', i.e. correlations between signals from LOFAR stations. Converting these observations into sky maps (images), which are needed for astronomy research, can be challenging due to the data sizes of the observations and the complexity and compute requirements of the software involved. Using the PROCESS software environment and testbed, we enable a simple point-and-click-reduction of LOFAR observations into sky maps for users of this archive. This work was performed as part of the PROCESS project which aims to provide generalizable open source solutions for user friendly exascale data processing.

Keywords

MSC

68-04

Cite this article

@article{cai-5332,
  author  = {Souley Madougou and Hanno Spreeuw and Jason Maassen},
  title   = {Processing Radio Astronomical Data Using the PROCESS Software Ecosystem},
  journal = {Computing and Informatics},
  volume  = {39},
  number  = {4},
  pages   = {838--859},
  year    = {2020},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2020_4_838}
}
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