Photometry+: A Scientific Pipeline and Teaching Tool
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Authors
Tudor, Alexis Renee
Issue Date
2021
Type
Thesis
Language
Keywords
Astronomy , Differential Photometry , Human-computer interaction , Photometry , Python , UX Design
Alternative Title
Abstract
As more and more data are collected from the night sky, it becomes increasingly important to be able to analyze the data precisely and quickly by using computer programs. Given the importance of data analysis pipelines for telescopes we have developed a photometric pipeline, Photometry+, for the Great Basin Observatory (GBO), a 0.7-meter robotic telescope located in the Great Basin National Park in Nevada. This photometric pipeline takes raw images of the night sky and measures the magnitude of a star in the image. Studying the changes in the flux of a star over time is crucial for learning more about variable objects such as supernovae and binary star systems. Photometry+ focuses on human-computer interaction (HCI) in addition to scientific results. The HCI goals of the proposed pipeline are to create a graphical user interface (GUI) that is easy to use, gives astronomers control of and confidence in the results of the program, and teaches students the process of differential photometry through use. Our research shows that users agree that these goals are met and that just using Photometry+ results in a statistically significant 15% increase in score on a differential photometry quiz (from 66% to 81%). These results cement it as a new tool for professional astronomers looking to reduce the time they spend on data analysis while still obtaining publication-quality results and for students looking to learn the process alike. This thesis encompasses astronomy and human-computer interaction background, related works, software engineering aspects, practical astronomy uses of Photometry+, the user study research we completed, and the results we obtained.