Critical Noise Treatment Algorithm

Astronomers of India have developed algorithms that can improve the accuracy of data from the outer planets by reducing interference from the Earth’s atmosphere, the effects of equipment, and various other factors

Highlights

At the Indian Institute of Astrophysics, a team of researchers have developed algorithms with the aim to improve exoplanets data accuracy. Algorithms known as critical noise processing algorithms improve the accuracy of data by reducing signal pollution by the Earth’s atmosphere and interference from equipment and other factors. This allows scientists to investigate the environment of exoplanets more closely.

The study has been published in the Astronomical Journal which is a peer-reviewed scientific journal and is published by the American Astronomical Society.

About the study

Known as the Critical Noise Treatment Algorithm, this algorithm helps to study the perimeter of extrasolar planets in more detail. A complete understanding of the physical properties of exoplanets will help one study exoplanets that may be habitable because they resemble the planet Earth. To this end, a group of astronomers at the Indian Institute of Astronomical Physics in Bangalore used data from ground-based optical telescopes and Transiting Exoplanetary Exploration Satellites or TESS space telescopes.

Importance of studying Exoplanets

The planets which exists outside the solar system we are in are known as exoplanets. NASA’s TESS was developed with the aim of searching for various exoplanets using the transit method. This method looks to indirectly detect the presence of extrasolar planets in star orbit using photometry, which measures the intensity of light in relation to the brightness perceived by the human eye.

If the exoplanets physical properties are very accurately understood, astronomers may come across potentially habitable exoplanets such as the Earth. With this in mind, IIA astronomers used TESS data and terrestrial optical telescopes which are available in India for their research.

Researchers received signals from the outer planets using the Jagdish Chandra Bhattacharya Telescope at Vainu Bappu Observatory located in Kavalur in the state of Tamil Nadu and the Himalayan Chandra telescope at the Indian Observatory in Hanle located in Ladakh.

Usefulness of Critical Noise Treatment Algorithm

Astronomers have used the photometric transit method to obtain photometric data from several planets that host the stars, the study states. The photometric transit method is a method of measuring the diminishing of star light caused by a planet in a particular orbit. The orbits are aligned so that the planets move regularly between their host stars and the telescopes observing them. Photometric transit observations show the size of the planet and its orbital time. Noise generated by various sources confuses transit signals and poses challenges in accurately estimating the physical parameters of extrasolar planets. Studies show that the critical noise processing algorithm can process pass signals captured by ground-based and space telescopes with much higher accuracy than before.

Astronomers have used algorithms to reduce equipment noise and interference caused by host star fluctuations and pulsations. Pulsation is a phenomenon of changes in the brightness of a variable star caused by changes in the area and temperature of the surface layer of the variable star.