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Project area/S

  • Extragalactic Radio Science
  • Data Intensive Astronomy

Project Details

The Australian Telescope Compact Array (ATCA) is a six dish radio interferometer located in Narrabri, New South Wales. Since the early 1990’s it has been a cornerstone of radio-astronomy in the Southern hemisphere. In recent years it has performed a series of large observing campaigns, with aims of surveying large fields to new depths and resolutions. For fields of the sky that are larger than the field-of-view of a single observation, a technique called ‘mosaicing’ has to be deployed, which describes the process of stitching together nearby, smaller images into a single larger image. Although this can be a straight-forward process in the simple case of stitching individual images together as a post-processing step, for optimal results this mosaicing needs to be incorporated early into the image processing workflow. DDFacet, an advanced image processor written for the next-generation of radio-telescopes that has only been recently developed, has initially been applied to such ATCA datasets and have demonstrated exceptional improvements over traditional imaging approaches. This project aims to further investigate this imaging approach, with goals of:

  • Creating a initial set of images using DDFacet
  • Writing a miniaturized pipeline capable of being deployed on supercomputers
  • Verify image and source finding outputs for reliability

The project has multiple datasets that have already been collected and are available for processing including:

  • 200 pointings over 250 hours at 6.7 and 9.5 GHz covering the Extended Chandra Deep Field South
  • 4000 pointings over 250 hours at 5.5 and 9.0 GHz covering the Small Magellanic Cloud
  • 7000 pointings over 3000 hours at 5.5 and 9.0 GHz covering the Galaxy And Mass Assembly 23-hour field.

Student Attributes

Academic Background

A background in computing or astronomy is preferred.

Computing Skills
Understanding of bash and python is desirable

Training Requirement
Python, bash, slurm/HPC environments, parallel processing

Project Timeline

  • Week 1 Inductions and project introduction
  • Week 2 Initial presentation
  • Week 3 Acquire data, initial tests with single pointing
  • Week 4 Single pointing analysis, self-calibration
  • Week 5 Small set of pointings (~10), self-calibration
  • Week 6 Small set of pointings (~10), self-calibration and analysis
  • Week 7 Larger set of pointings (>100), self-calibration and analysis
  • Week 8 Larger set of pointings (>100), self-calibration and analysis
  • Week 9 Final presentation
  • Week 10 Final report


Dr Natasha Hurley-Walker

Senior Lecturer

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Dr Minh Huynh

Adjunct Senior Research Fellow

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