USE CASES

Transient astrophysics with a sq kilometre array pathfinder (taska)

The Sun occasionally enters periods of high activity, sometimes releasing powerful bursts of highly energetic elementary particles that could have dramatic consequences for Earth. These solar bursts can lead to power grid failure, damage to electrical circuits, disruption of radio communication and GPS, interference with civil aviation, and more, all of which can severely disrupt daily life.

However, early detection and prediction of such events can provide critical time to prepare for their impacts. Remote observation of “space weather” allows for preventative action to be taken as a solar burst approaches Earth, such as temporarily shutting down key electrical systems to protect them from damage.

 

The last generation of radio telescopes (as well as space-borne probes) allow us to detect and quantify incoming solar bursts through their signature emitted as radio waves, as soon as they are emitted from the Sun. The remote signal measured from solar bursts can be turned into dynamic movies showing the evolving structure with time (around the Sun) and with frequency (as a sound spectrogram). This information allows researchers to evaluate potential  threats with regard to solar of burst size, energy and trajectory crossing Earth orbit. 

The TASKA Use Case

The EXTRACT project is harnessing the power of data in its space case that tests EXTRACT project technology in a Transient Astrophysics with a Square Kilometre Array Pathfinder (TASKA) case using NenuFar radio telescopes in Nançay, France. EXTRACT project technology helps filter raw data from these telescopes by a factor of 100 to allow meaningful data to be populated into high-quality datasets.

The use case aims to develop the different aspects and technical solutions for building a fast-response system that will identify the presence and morphology of the bursts using trained Machine Learning/Deep learning (ML/DL) networks deployed on cloud architectures.

Currently, more than 2000 antennas in Nançay, France are receiving 56TB of raw data on solar activity per day. Two activities are being pursued to effectively mine and analyse this vast amount of information at the source for early detection, prediction and further research:

  • Activity A: “A”gile detection of solar activity and decision making for reduction of raw data
  • Activity C: “C”loud-based fast-paced data calibration and imaging.

TASKA aims to answer multiple questions:

  • How can we efficiently detect and model the various solar radio emissions from observation with radiotelescopes?  
  • How can we develop an automatic data processing and identification system that will enable quick response time to derive burst parameters and location from near real-time?
  • How can ML/DL in a Cloud-based framework contribute to the deployment of such alert systems?

EXTRACT technology will be used to:

  • Optimize current data infrastructures and AI & Big-data frameworks to facilitate the development of complex data-mining workflows, including data processes and analytics methods
  • Develop novel data-driven orchestration techniques to select the most appropriate set of computing resources to jointly address extreme data characteristics
  • Increase the interoperability of programming paradigms and execution models used across the compute continuum.

Learn more about the TASKA use case

*The NenuFAR telescope clips used in the videos were provided by Observatoire de Paris, CNRS PSL & Oak Productions, 2017.

Read more about this case: