Different telescopes work at different wavelengths, meaning they can observe different objects in the sky — and when data from various telescopes is combined, it can make for stunning views that would be impossible to get from any one instrument. That’s the case with a beautiful new image of a cluster of thousands of galaxies that combines data from both the Hubble Space Telescope and the James Webb Space Telescope to create a stunning and colorful view.
Hubble looks in the optical wavelength, like the human eye, and the galaxies that it detected are mostly shown in blue and cyan. James Webb, however, looks beyond the range of human vision in the infrared wavelength, and the galaxies it viewed are shown mostly in yellow and red. There’s some crossover in the green parts of the image, which represent portions of the spectrum visible to both telescopes.
The huge MACS0416 cluster is actually a pair of galaxy clusters that are in the process of colliding, and which will eventually form one enormous cluster. This cluster was studied by Hubble over the last decade to look for some of the furthest galaxies that had been detected at that time — work that has now been taken up by Webb.
“We are building on Hubble’s legacy by pushing to greater distances and fainter objects,” said lead researcher Rogier Windhorst of Arizona State University in a statement.
In addition to producing a stunning image, the Webb data is also helping to investigate objects that change their brightness over time, called transients. These could be supernovae events, when a star comes to the end of its life and explodes in a large, bright event that quickly dims, or they could be other types of object such as stars or galaxies that are briefly magnified due to the effect of gravitational lensing. There were 14 of these transient objects identified in the image.
“We’re calling MACS0416 the Christmas Tree Galaxy Cluster, both because it’s so colorful and because of these flickering lights we find within it. We can see transients everywhere,” said fellow researcher Haojing Yan of the University of Missouri.
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