Event Title

Calculating the Kepler Detection Efficiency -- A Data Analysis of the Kepler Main Mission

Advisor(s)

Dr. Eric Hawker, Illinois Mathematics and Science Academy

Location

Room A115

Start Date

26-4-2019 9:45 AM

End Date

26-4-2019 10:00 AM

Abstract

The main focus of this study is to roughly estimate the number of earth-sized habitable planets within the Milky Way galaxy. Along with this, we will determine the detection efficiency of the Kepler space telescope. We already know the number of earth-sized planets that were detected by Kepler. However, the Kepler telescope’s instruments are not perfectly precise, and in order to measure its efficiency, we will put in the data of a fake planet into the Kepler’s star luminosity files and see if its transit gap is detectable. We will analyze the Kepler luminosity data by either looking at the visualized graphs, or putting it through a machine learning algorithm. Using the analysed data, we can determine the actual number of potential earth-like habitable planets in the Milky Way, including those which were not detected by Kepler. We will look at various characteristics of planets to determine their habitability: luminosity of the parent star(s), planet radius, orbital radius, and orbital inclination. From the planet radius we can estimate the mass and density of the planet, which will also help us determine its habitability. These calculations will create an accurate estimate of the number of potential earth-like habitable planets within the Milky Way galaxy.

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Apr 26th, 9:45 AM Apr 26th, 10:00 AM

Calculating the Kepler Detection Efficiency -- A Data Analysis of the Kepler Main Mission

Room A115

The main focus of this study is to roughly estimate the number of earth-sized habitable planets within the Milky Way galaxy. Along with this, we will determine the detection efficiency of the Kepler space telescope. We already know the number of earth-sized planets that were detected by Kepler. However, the Kepler telescope’s instruments are not perfectly precise, and in order to measure its efficiency, we will put in the data of a fake planet into the Kepler’s star luminosity files and see if its transit gap is detectable. We will analyze the Kepler luminosity data by either looking at the visualized graphs, or putting it through a machine learning algorithm. Using the analysed data, we can determine the actual number of potential earth-like habitable planets in the Milky Way, including those which were not detected by Kepler. We will look at various characteristics of planets to determine their habitability: luminosity of the parent star(s), planet radius, orbital radius, and orbital inclination. From the planet radius we can estimate the mass and density of the planet, which will also help us determine its habitability. These calculations will create an accurate estimate of the number of potential earth-like habitable planets within the Milky Way galaxy.