ExoMiner++: Artificial intelligence in exoplanet discovery
Why in news
NASA has developed ExoMiner++, an advanced deep-learning AI model to identify exoplanets from space telescope data, significantly improving the speed, scale, and reliability of planet detection.
What is ExoMiner++
ExoMiner++ is an explainable artificial intelligence model designed to detect exoplanets by analysing telescope brightness data.
It is the successor to ExoMiner, which was used on data from the Kepler Space Telescope.
ExoMiner++ can also analyse data from the Transiting Exoplanet Survey Satellite (TESS).
How it works
Uses light curves (graphs of a star’s brightness over time).
When a planet transits in front of a star, it causes a temporary dip in brightness.
The key challenge is distinguishing true planetary transits from false positives, such as:
Binary star systems
Background stellar objects
Instrumental noise
Key features of ExoMiner++
Explainable AI
Unlike black-box models, ExoMiner++:
Assigns a probability score indicating the likelihood of a signal being a planet
Explains why a particular classification was made
Enhances scientific trust and validation.
Improved capability
Trained on both Kepler and TESS datasets
Can analyse a much larger number of stars simultaneously
Improves detection in cases where signals are ambiguous or noisy
Achievements so far
ExoMiner (earlier version):
Validated 370 new exoplanets from Kepler data
Focused on candidates stuck in validation limbo
ExoMiner++:
Has identified around 7,000 potential exoplanet candidates from TESS data (as of now)
Open science and future missions
ExoMiner++ has been released as open-source software on GitHub.
Researchers worldwide are invited to:
Replicate NASA’s results
Apply the model to independent datasets
Improve the algorithm
The model is expected to support future missions such as the Nancy Grace Roman Space Telescope.
Prelims Practice MCQs
Q. With reference to ExoMiner++, consider the following statements:
It is an artificial intelligence model developed by NASA for exoplanet detection.
It analyses gravitational waves to identify planets outside the solar system.
It is designed as an explainable AI system.
Which of the statements given above are correct?
(a) 1 and 3 only
(b) 1 only
(c) 2 and 3 only
(d) 1, 2 and 3
Answer: (a)
Explanation:
Statements 1 and 3 are correct.
Statement 2 is incorrect: ExoMiner++ analyses light curves, not gravitational waves.
Q. ExoMiner++ primarily uses which of the following methods to detect exoplanets?
(a) Direct imaging of planetary surfaces
(b) Measurement of stellar brightness dips during planetary transits
(c) Detection of radio signals from alien civilizations
(d) Observation of asteroid belts
Answer: (b)
Explanation:
The transit method identifies planets by observing periodic dips in a star’s brightness.
Q. Consider the following space missions:
Kepler Space Telescope
Transiting Exoplanet Survey Satellite (TESS)
Nancy Grace Roman Space Telescope
Which of the above are associated with exoplanet research?
(a) 1 and 2 only
(b) 2 and 3 only
(c) 1 and 3 only
(d) 1, 2 and 3
Answer: (d)
Explanation:
All three missions contribute or will contribute to exoplanet research.