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This artist's illustration shows the planetary system K2-138, which was discovered by citizen scientists in 2017 using data from NASA's Kepler space telescope.

After the first exoplanet was identified almost three decades earlier, in 1992, humanity has come a long way in terms of exoplanet discovery. As of today, we have spotted over 4000 validated exoplanets that revolve around their respective suns.

Exoplanets are celestial bodies that exist outside our vast solar system. Equipped with cutting-edge technology, many research groups have been identifying these exoplanets left, right and centre.

However, for the first time ever, 301 validated planets were added to the ever-growing exoplanet tally all at once!

Wondering how? The US space agency NASA reported that a new deep neural network called 'ExoMiner' was responsible for this incredible scientific feat.

The ExoMiner leverages NASA's Pleiades supercomputer and, like any deep neural network, can automatically learn a task when provided with enough data. ExoMiner is designed with various tests, properties human experts use to confirm new exoplanets, past confirmed exoplanets, and false-positive cases in mind. Thus, it could tell apart actual exoplanets from imposters, making this technology and its predictions highly reliable.

"Unlike other exoplanet-detecting machine learning programs, ExoMiner isn't a black boxthere is no mystery as to why it decides something is a planet or not," said Jon Jenkins, an exoplanet scientist at NASA's Ames Research Center in California's Silicon Valley. "We can easily explain which features in the data lead ExoMiner to reject or confirm a planet."

It is a highly tedious process to comb vast datasets from missions like Kepler, which has hundreds of stars in its range of view, each with the potential to house numerous possible exoplanets. In such cases, the ExoMiner is the perfect substitute as it reduces the burden of astronomers in sifting through data and determining what is and isn't a planet.

"When ExoMiner says something is a planet, you can be sure it's a planet," said Hamed Valizadegan, ExoMiner project lead and machine learning manager with the Universities Space Research Association at Ames. "ExoMiner is highly accurate and in some ways more reliable than both existing machine classifiers and the human experts it's meant to emulate because of the biases that come with human labelling."

NASA said that all 301 machine-validated planets were originally detected by the Kepler Science Operations Center and were promoted to planet candidate status by the Kepler Science Office. But until ExoMiner, no one was able to validate them as planets.

And while none of the newly discovered planets is thought to be Earth-like or in their parent stars' habitable zones, they share some traits with the rest of the verified exoplanet population in our galaxy.

According to Jon Jenkins, the 301 discoveries will help researchers better understand planets and solar systems beyond our own and what makes ours so unique.

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ExoMiner Goes Planet Hunting! NASA's Machine Learning Network Validates 301 New Exoplanets at One Go | The Weather Channel - Articles from The Weather...