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Young Gas Giant Discovered in Old Data: Direct Imaging Reveals 5× Jupiter Exoplanet

Young Gas Giant Discovered in Old Data: Direct Imaging Reveals 5× Jupiter Exoplanet
Researchers at NMSU and Northwestern University discover new exoplanet

Scientists at New Mexico State University and Northwestern University reanalyzed almost decade-old imaging data and directly detected a new exoplanet. The planet is a gas giant about five times the mass of Jupiter, roughly 400 light-years away, and only ~13 million years old. This direct-imaging discovery is rare and helps astronomers refine techniques needed to search for smaller, potentially Earth-like planets.

Researchers at New Mexico State University and Northwestern University have identified a previously unnoticed exoplanet by reanalyzing nearly decade-old imaging data. Using direct imaging techniques applied to archival light-level measurements, the team pulled a faint planetary signal from the data and confirmed a new world in the Milky Way.

The object is a gas giant roughly five times the mass of Jupiter, located about 400 light-years from Earth and orbiting a binary star system. At an estimated 13 million years old, the planet is extremely young compared with most known exoplanets.

Why This Matters

Direct imaging of exoplanets is uncommon — only a few dozen have been detected this way — because it requires isolating extremely faint planetary light from the much brighter starlight. Finding a Jupiter-like planet through direct imaging gives astronomers a valuable test case to refine the data-reduction and analysis techniques needed to search for smaller, potentially habitable worlds in the future.

"The technology you need, the data reduction, the data analysis techniques you need to find Earth-like planets; we’re really testing them right now with the relatively easier Jupiter-like planets," said Eric Nielsen, Assistant Professor of Astronomy at NMSU.

Researchers caution that the capability to detect truly habitable planets remains years away, but say this discovery represents a meaningful step forward in developing the methods and tools needed for that goal.

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