Applied Fast Fourier Transformation, Data Normalization, and deployed machine learning models to determine which stars beyond our solar system have planets orbiting them.
There are billions of galaxies in the universe. These galaxies have millions of stars. One such galaxy is the Milky-way galaxy in which our solar system exists. The solar system has a star called Sun which has its own light. In astronomy, a star is a heavenly body which has its own light. There are 8 planets in our solar system orbiting around the Sun. Similar to this, in some other galaxy there would be a star and probably a planet would be revolving around that star. Long ag0, NASA placed a telescope called Kepler telescope in the space. This telescope is used to measure the brightness of the stars in the far-distant galaxies.
Whenever a planet, while orbiting its star, comes in between the telescope and the star, the brightness of the star recorded by the telescope is lower whereas when the planet goes behind the star, the brightness of the light recorded by the telescope is higher. This method of detecting exoplanets in far-distant galaxies through the brightness of the light emitted by a star is called the Transit Method.
Essentially, if you plot the brightness on the vertical axis and the time on the horizontal axis, then you will see that the brightness of the star recorded by the telescope increases and decreases periodically. Thus, in the graph, you will notice a wave-like pattern. This indicates that the star definitely has at least one planet.