Indian Astronomers Develop Special Algorithm To Understand Exoplanets More Accurately
The critical noise treatment algorithm developed by astronomers from the Indian Institute of Astrophysics increases the accuracy of exoplanet data
New Delhi: A team of Indian astronomers from the Indian Institute of Astrophysics (IIA) has developed an algorithm that increases the accuracy of data from exoplanets. The algorithm, called the critical noise treatment algorithm, improves the accuracy of data by reducing the contamination in signals caused by Earth's atmosphere, and disturbances resulting from Instrumental effects and other factors. This allows the environment of exoplanets to be studied with better precision.
The study, led by Professor Sujan Sengupta of IIA, was recently published in the Astronomical Journal, a peer-reviewed scientific journal by the American Astronomical Society (AAS).
Why Is It Important To Study Exoplanets?
Exoplanets are planets existing outside our solar system. NASA's Transiting Exoplanet Survey Satellite (TESS) is designed to search for exoplanets using the transit method. The transit method aims to indirectly detect the presence of exoplanets in orbit around a star, using photometry, which is the measurement of light intensity in terms of perceived brightness to the human eye.
If the physical properties of exoplanets are understood with extreme accuracy, astronomers may come across an exoplanet similar to Earth, which may be habitable. With this goal in mind, the astronomers at IIA have been using TESS data, and ground-based optical telescopes available in India to conduct their research, the Union Ministry of Science and Technology said in a statement.
The researchers have been using the Himalayan Chandra Telescope at Indian Astronomical Observatory, Hanle, Ladakh, and the Jagdish Chandra Bhattacharya Telescope at Vainu Bappu Observatory, Kavalur, Tamil Nadu, to obtain signals of exoplanets, the study mentions.
How Is The Critical Noise Treatment Algorithm Useful?
The astronomers have obtained photometric data from several planet hosting stars using the photometric transit method, the study states.
The photometric transit method is a technique which measures drops in starlight caused by planets having a specific type of orbit. The orbits are oriented in a way such that the planets periodically pass between their host stars and the telescope observing them.
Photometric transit observations reveal the sizes of planets as well as their orbital periods.
Noise created due to various sources disrupts the transit signals, posing a challenge to accurately estimate the physical parameters of exoplanets.
The critical noise treatment algorithm has the ability to treat the transit signals detected by both ground- and space-based telescopes with a precision much higher than before, the study states.
Professor Sengupta, along with his student Suman Saha, recently demonstrated the effectiveness of the algorithm, said the statement. With the help of the algorithm, they critically analysed the signals of Exoplanet KELT-7 band and other data obtained using TESS.
The astronomers used the algorithm to reduce instrumental noise and disturbances arising from the variability and pulsation of host stars. Pulsation is the phenomenon of variation in the brightness of a variable star, caused by changes in the area and temperature of the star's surface layers.
They also accurately estimated the physical parameters of Exoplanet WASP-43 b, and Exoplanet HAT-P-54 b with the help of the algorithm, the study mentions.
Signals of Exoplanet WASP-43 b were obtained by using the Jagadish Chandra Bhattachayya Telescope.
The Himalayan Chandra Telescope was used to obtain signals of Exoplanet HAT-P-54 b.
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