PyExoplanets: A Computed Application for Detecting Exoplanet Transits on Stars’ Light Curves Authors Noora J. Al-Muftah (CS 2016)
Faculty Advisor Saquib Razak, Ph.D.
Category Computer Science
Abstract
One way of detecting extrasolar system planets (planets that orbit stars outside our solar system) is by the transit method. In this method, astronomers use the light curves (plot of the brightness of a star over a period of time). If a decrease in the brightness of the star is noticed in the light curve, then it can be further deduced if it is caused by an object (planet) that blocks the star’s emitted light by passing in front of it. Projects like NASA’s Kepler mission produces thousands of stars’ light curves searching for exoplanets. One resulting problem is that it is difficult and time consuming to analyze all of these light curves one by one. For my project, I have developed an astronomical data analysis application that can shorten the process of finding transits by applying an image analysis method on the graph of the light curve. In my application, PyExoplanets, I selected light curve data from the Kepler mission FITS files for planetary-candidate stars observed in the Q3 quarter set. My application was developed using Python, the Python Image Library for analyzing the light curve image, PyFITS for reading FITS files, Matplotlib for plotting the star’s data, and Visual Python for producing simple 3D animation of the star and the exoplanet. My project is an initial step in creating a complete computer application that can potentially assist astronomers in the process of finding exoplanets.
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