The telescope suffers from blurred vision.
But a team of Australian researchers created a AI algorithm This solves the problem – a huge relief for the scientific community, which hopes to use the device to discover exoplanets around the stars in our galaxy Galaxy.
The instrument affected is the Aperture Masking Interferometer (API), designed and built by a team of astronomers led by Professor Peter Tuthill of the University of Sydney in Australia. API is not one of the main four tools James Webb Space Telescope (JWST) but an instrument that enables a special type of imaging on one of the observatory’s main instruments – the Near-Infrared Imager and Slitless Spectrograph (NIRISS).
The API allows NIRISS to combine light from different sections of the telescope’s main mirror to increase the sensitivity and resolution of the instrument. The API component, consisting of an opaque mask with seven holes, was specifically designed to observe small and faint distant exoplanets. StarsBut when astronomers turned on the instrument for the first time, they found that the images were coming out blurry.
The issue was reminiscent of a major flaw in the optics of Webb’s predecessor. Hubble Space TelescopeWhich was shown to be clearly near-sighted after reaching orbit in 1990. Hubble’s defect was caused by imperfections in its primary mirror, and required a crewed space mission to fix it, at a cost of hundreds of millions of dollars. In 1993, a team of astronauts placed a set of corrective mirrors in front of the telescope’s sensor so that it could produce images of the expected quality.
However, such a mission is out of the question for the Web. Hubble orbits about 320 miles (515 kilometers) above Earth, barely 70 miles (110 kilometers) above Earth. International Space StationHowever, Webb is at a distance of 930,000 miles (1.5 million km) with the planet, more than three times further away than Earth. MoonNo human space mission has flown that far.
The blurring in Webb’s API images was discovered to be caused by electronic distortions occurring on Webb’s infrared camera detector.
To fix the problem, former University of Sydney Ph.D. students Max Charles and Louis Desdoites have developed a neural network, a type of AI algorithm inspired by the functioning of the human brain, that detects and corrects pixels affected by electrical charges that distort observations.
The algorithm, called AMIGO (for Aperture Masking Interferometry Generative Observations), has worked remarkably well.
“Instead of sending astronauts out to bolt on new parts, they managed to fix things with code,” Tuthill said. in a statement,
The researchers demonstrated AMIGO’s sharpening skills on images of a dim exoplanet and a very cool, low-mass star (a red-brown dwarf) around 133. light years from Earth. In another imaging campaign, API, with the help of AMIGO, was able to produce detailed images of a black hole jet, volcanic surface Jupiter’s moon Ioand stellar winds from distant variable stars.
“This work brings the JWST approach even more into focus,” Desdoigts, now a postdoctoral researcher at Leiden University in the Netherlands, said in the statement. “It is incredibly rewarding to see how a software solution expands the scientific reach of the telescope.”
The James Webb Space Telescope, operational from July 2022, has revolutionized astronomy by revealing unexpected details about the formation of early galaxies and black holes. It has also made important contributions to the study of exoplanets, providing unprecedented measurements of the composition of their atmospheres. Now with the API at full speed, the web is ready for even more amazing discoveries.
