Exoplanets is the term used for planets beyond our solar system, those that orbit stars other than our Sun. Astronomers have confirmed detections of over 5,000 exoplanets, and another 8,000+ candidates. For the latest numbers, go here.
In a few cases, the orbit of an exoplanet happens to be in position that the planet passes through our line of sight. This is to say, the planet blocks part of the star’s light once during each orbit.
These are called transiting planets.
Telescopes can do more than take pictures–their electronic detectors gather light; and the digital images derived from this electronic data contain information about the amount of light reaching the telescope from each star.
Planets do not shine with visible light of their own, and are so dim and small compared to the stars they orbit, it is only in very rare circumstances that we can use current telescopes to detect these planets directly.
Even a small telescope, is sensitive enough to detect a some drop in the amount of light reaching the telescope when the image is taken.
For the reduction of my lightcurves, some of the tools I used for this research included Python coding with "EXOTIC" which stands for EXOplanet Transit Interpretation Code, through Google Colab or Jupyter Notebooks.
To “reduce” a light curve means to extract the data I'm interested in, from a large set of images. Part of this process also included creating a star chart manually in order to help the coding system to find the desired target. A comprehensive star chart can be created by using the American Association of Variable Star Observers (AAVSO) plotter.
My first AAVSO star chart and field of view with target and comp stars
One of my first lightcurve reductions shown here, of target HAT-P-54 b.
Part of this process included calculating values such as transit depth in (Rp2/Rs2), transit depth uncertainty, mid-transit and mid-transit uncertainty and sigma values.
O-C Plots and the Posterior Distributions of the Updated Mid-Transit Times and Period
"Observed - Computed Plot"
The Gaussian histogram tells us the value that a parameter could be while still fitting the data. The width of the distribution tells us there is some level of uncertainty in the measurement.
The circular boxes tell us how different parameters are correlated with each other, and the more circular it is, the more independent the two parameters are.
My O-C Plots as example for visualization
Though interesting, exoplanets were never a particular area of focus for me. It became a really big part of my day to day for quite a while, and I look forward to what this area of Astronomy will bring us in the future with future ground and space based observation.