Oct 24, 2016 | Updated: 09:37 AM EST

NASA Weighs Ancient Galaxy Using Data From Different Telescopes

Jan 11, 2016 11:27 PM EST

Astronomers had weighed an ancient galaxy using data collected from NASA's orbital telescopes. The galaxy is named IDCS J1426.5+3508 (IDCS 1426) and is considered the largest structure of its kind during the period.

NASA used three of its orbital telescopes to weigh IDCS 1426, a galaxy that is "visible" from Earth on its form approximately 3.8 billion years ago. IDCS 1426 was located 10 billion light-years away from Earth. It has been estimated that this galaxy has a mass of 500 trillion times that of the Sun, or equivalent to 1,000 Milky Ways.

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Scientists believe that an analysis of these clusters could lead to better understanding of how galaxies in the universe came to form during its early phase. The data used in this study are gathered from NASA's Spitzer and Hubble telescopes. The Chandra X-ray Observatory and the Keck Observatory in Mauna Keo, Hawaii, also provided critical parts of the data.

The space agency was able to calculate the IDCS 1426's mass itself using three independent techniques. One of these methods was astronomers observing the imprint of the mass of the ancient galaxy made on the cosmic microwave background radiation. Another method was measuring the mass needed to confine the X-ray discharging gas to the cluster. The final method was observing the extent of the light from galaxies that were situated behind IDCS 1426 that was being distorted because of the cluster's mass.

With this current set of models, it is expected that galaxy clusters take many billion years before they fully coalescence. The vast distance between Earth and IDCS 1426 means that the latter was only 3.8 billion years old (relatively young for a galaxy).

"The presence of this massive galaxy cluster in the early Universe doesn't upset our current understanding of cosmology," Anthony Gonzalez of the University of Florida in Gainesville, Florida, who co-authored a paper on the research, said. "It does, however, give us more information to work with as we refine our models," he iterated. 

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