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The Exploration of Habitable Exoplanets using Data Mining Algorithms and Data Manipulation
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Abstract:
The NASA Exoplanet Archive is a dataset that is an extraction from the total sets of data from the Keck, Kepler, TESS, and Gaia observations, where observations show that the observed stellar objects have been determined to possess one or more planets. It is continually updated as more and more exoplanets, or planets outside our own solar system, are discovered and documented. Our first objective was to see how many of these entries were duplicates, which would bring the total number of entries we would work with from 29,283 to 4,259. In previous research, this dataset was filtered by determining which of these exoplanets are inside their Circumstellar Habitable-Zone (CHZ), commonly defined as the range of distance from a host star such that a planet may contain liquid water, a key requirement for life as we know it. However, this calculation was done only for exoplanets with M-type host stars. Over the course of our research, we were able to expand this calculation of the CHZ to exoplanets with host stars of all spectral types. We performed more in-depth investigation of planets with G, K, and M types stars by comparing them to planets in the Planetary Habitable Laboratory (PHL) exoplanet dataset to see how many similarities there are. The PHL catalog used its own set of criteria to define those planets in it as habitable. Using this method, we determined that there were 3 exoplanets with M-type host stars, 0 exoplanets with a G-type host star, and 1 exoplanet with a K-type host star.

Application of Data Mining to Search for Potentially Habitable Exoplanets
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Abstract:
Many light years away from our own solar system, over four thousand confirmed planets orbit stars in a fashion similar to our own eight planets and the sun. With the discovery of these planets, called “exoplanets,” comes the question of extraterrestrial life, a concept scientists have been exploring for years. The possibility of exoplanetary habitability relies on a number of factors, such as spectral type, density, and eccentricity, but most importantly: whether the exoplanet in question contains water, the fundamental requirement for life, as we know it, to exist. To determine whether an exoplanet provides the ideal conditions for sustaining this vital ingredient for life, we considered the concept of the Goldilocks Zone, or the circumstellar habitable zone (CHZ)—the range of orbits around a star where liquid water is capable of existing. The research we have been conducting this summer utilizes the public dataset provided by NASA and Caltech and data mining methods, including Python and Microsoft Excel, to identify exoplanets with potentially habitable conditions. The discovery of the exoplanet K2-18b’s water vapor-containing atmosphere was a major part of our research, in which we focused on identifying exoplanets with similar attributes to that of K2-18b, in hopes that they too may be able to retain atmospheric water vapor. After a two-month period, we discovered that 59 exoplanets orbit in the CHZ of their host star. As for the K2-18b ruleset, only 1 planet, K2-3d, satisfies the conditions. We believe K2-3d to have a high degree of similarity to K2-18b, but more in-depth analysis will have to be conducted to conclude its potential to support atmospheric water vapor and life as we know it.

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