An SNR is a remnant of an explosion from a dying star. A supersonic blast sends material hurtling out into the interstellar medium at supersonic speeds, compressing and heating gases and objects along the way.
A new supercomputer in Australia has been turned on, and researchers have processed a series of radio telescope observations, including this highly detailed image of a supernova remnant.
New-generation radio telescopes such as ASKAP (Australian Square Kilometer Array Pathfinder) produce enormous amounts of data at very high rates, which requires powerful software running on supercomputers.
In this situation, Pawsey Supercomputing Research Center comes to the rescue with Setonix, a supercomputer named after the quokka (Setonix brachyurus, and one of the cutest animals you’ll ever see) of Western Australia.
Australia’s national science agency, CSIRO, operates ASKAP, a telescope consisting of 36 satellite dishes operating as one. The observational data is transferred via optical fibers to the Pawsey Center to be processed and transformed into science-ready images using high-speed optical fibers.
ASKAPsoft processing software has now been integrated into Setonix, marking a milestone on the road to full implementation.
One of the amazing images is that of a cosmic object called G261.9+5.5, a supernova remnant. Between 10,000 and 15,000 light years away, it is estimated to be over a million years old. In 1967, CSIRO radio astronomer Eric R. Hill classified this object in our galaxy as a supernova remnant using observations from CSIRO’s Parkes radio telescope.
An SNR is a remnant of an explosion from a dying star. A supersonic blast sends material hurtling out into the interstellar medium at supersonic speeds, compressing and heating gases and objects along the way.
Here is a brand new image by Australia’s brand new supercomputer, Setonix. Check out supernova remnant G261.9+5.5! Data from our #ASKAP radio telescope was processed on Setonix by the @CSIRO Science Data Processing team alongside the @PawseyCentre team. pic.twitter.com/pfRRupRYZU
— CSIRO_ATNF (@CSIRO_ATNF) August 8, 2022
(To the upper right side of the supernova we see a radio lobe galaxy ejecting jets of particles from its very active black hole.)
They contain information about the history of the star that exploded as well as how the surrounding medium was affected by the explosion.
This deep ASKAP radio image reveals the structure of this remnant, thus opening up the possibility of studying the physical properties of the interstellar medium in unprecedented detail, such as magnetic fields and high-energy electron densities.
In fact, Setonix installation has only just begun, with the second phase scheduled to be completed later this year, allowing teams to process more of the immense amounts of data that come from many projects in a fraction of the time.
Thus, researchers will be able to better comprehend our Universe, as well as discover new hidden objects in the radio sky. With Setonix, we will be able to explore a wide range of scientific questions in a shorter amount of time.
Setonix’s increased computational power benefits not only ASKAP but also all researchers across all fields of science and engineering. In parallel with the supercomputer’s full operation, ASKAP is completing a series of pilot studies and will soon begin even larger and more in-depth studies of the skies.
It is a complex exercise to process data even with a supercomputer since it can result in a variety of potential issues based on the processing mode used. As an example, the SNR image was created by combining hundreds of different frequencies (or colors, if you prefer), creating a composite image.
The individual frequencies, however, also hold a treasure trove of information. In order to extract that information, it is often necessary to create images for each frequency, which requires more computing resources and storage space.
This supernova remnant is just one of the many features revealed so far, and many more stunning images and discoveries of celestial objects are on their way.
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