Document Type

Conference Paper/Presentation


International Student Science Fair (ISSF) 2019 - March 18-22, 2019

Publication Date



The Large Synoptic Survey Telescope (LSST) is an 8.4 m telescope in Chile. It will observe ~37 billion objects in the night sky and, of these objects, more than 20 million will exhibit significant brightness variations, known as variable stars. There are many categories of variable stars, each providing valuable insights into different areas of astrophysics. Efficient algorithms are needed to classify these variable stars to better understand their nature and the formation history of the Milky Way galaxy. To improve the automated classification of variable stars, we have started a Zooniverse project, Stellar Sleuths. The Zooniverse is an online public portal to citizen science. Zooniverse volunteers can help us classify our content. The data given is in the form of light curves (stellar brightness versus time), and they can be used to determine if a star shows periodic variations in brightness. Stellar Sleuths provides light curves from the Asteroid Terrestrial-impact Last Alert System (ATLAS) to citizen scientists for classification. Currently, Stellar Sleuths only provides light curves to Zooniverse users. However, there is additional information (such as the temperature of a star) that can be used to aid the classification process. In this project we have experimented with the addition of supplemental information to add to the light curves for classification. We find that color-magnitude diagrams (CMDs) are useful for classifying variable stars. CMDs can be used to isolate stars in different stages of their lives. With data from the Gaia, a space-based telescope with an unprecedented ability to measure precise distances to stars, we can also place hundreds of millions of additional (normal) stars on the CMD as a reference to compare with a given variable star. Prior to April 2018, this information was poorly unknown, for many of these stars. Gaia distance measurements allow us to determine the intrinsic brightness of the stars that it observes. We find that CMDs significantly improve our ability to classify different variable stars. For example, RR Lyrae and Cepheid variable stars have very similar light curves, yet their positions in the CMD is completely different.



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