Home » Hubble captures the largest near-infrared image of space ever taken – Scientific Exploration – cnBeta.COM

Hubble captures the largest near-infrared image of space ever taken – Scientific Exploration – cnBeta.COM

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Hubble captures the largest near-infrared image of space ever taken – Scientific Exploration – cnBeta.COM

Don’t forget Hubble when you’re immersed in the excitement of discussing astronomy’s shiny new toy, the James Webb Space Telescope (JWST). JWST has been in the spotlight since its launch in late December, carrying the hopes and dreams of open-minded scientists, as well as gold-coated mirrors and a series of high-tech infrared cameras that can penetrate stardust and Help us solve the long-standing mystery of black holes.

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But the tried-and-true Hubble is still hard at work, and in fact, has just reached a sizeable milestone.

The Hubble Space Telescope, which entered the universe as far back as the 1990s, has captured its largest ever image of space in the near-infrared, which means it’s even dipping its toes into areas that the JWST is poised to explore.

This remarkable image could provide a glimpse into some of the rarest objects in the universe, such as monster galaxies that are the product of massive galaxy mergers or super-violent black holes lurking deep in interstellar space.

“It is very difficult to study these extremely rare events using existing imagery, which is what motivated the design of this large survey,” Lamiya Mowla, an astrophysicist at the University of Toronto, said in a statement. , who is also the first author of the research paper.

As part of a new high-resolution survey dubbed 3D-Dash, which stands for “drift and shift,” Hubble’s latest dataset spans an area of ​​the sky nearly six times larger than the moon seen from Earth. What you see is a mosaic of multiple Hubble photos that were later stitched together. Have to sigh, the area covered by this picture is quite spectacular.

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“Since its launch more than 30 years ago, the Hubble Space Telescope has led a renaissance in studying how galaxies have changed in the last 10 billion years of the universe,” Mowla said. “The 3D-DASH program expands on Hubble’s legacy in wide-field imaging, so we can begin to demystify galaxies beyond our own.”

What is an infrared image?

When looking up at the sky, even in the darkest forest canyons on Earth, you don’t see all the stars. It’s not because some stars are out of your sight.

They are there – only they are invisible.

The human eye can only see wavelengths of light in a certain region of the electromagnetic spectrum. Outside this area is infrared light. And those very, very distant galaxies and stars emit this type of light — so no matter how hard we try they’re basically hidden from our eyes.

But Hubble and the JWST have a way around our human limitations. The scientists embedded detectors of infrared light on the two instruments.

As you can see from the image, the JWST’s infrared capabilities are much more powerful — which is why it has the potential to show us a ton of things our eyes can’t see — but Hubble does have some special light-processing capabilities.

Also, Hubble actually has an advantage over JWST here.

According to the researchers behind the new study, the JWST is designed to take high-sensitivity close-up images of deep space, so it can get very clear pictures of small interstellar regions. This is incredible because we may get pictures of distant stars, galaxies, and other cosmic phenomena with a level of clarity similar to our images of space objects in close proximity to Earth.

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But Hubble can take extremely wide-field images like the new photos we humans are looking at. And this extensive dataset could ultimately inform future JWST studies, in addition to helping the next generation of scopes point in the right direction to reveal observations.

As Ivelina Momcheva, a data scientist at the Max Planck Institute for Astronomy and the study’s principal investigator, points out — “It gives us a glimpse into future scientific discoveries and allows us to develop new techniques to analyze these Large datasets.”

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