Toplogical Data Analysis Detects and Classifies Sunspots (Student Abstract)

Authors

  • Aidan Lytle UNCG, Greensboro, NC
  • Neil Pritchard UNCG, Greensboro, NC
  • Alicia Aarnio UNCG, Greensboro, NC
  • Thomas Weighill UNCG, Greensboro, NC

DOI:

https://doi.org/10.1609/aaai.v37i13.26997

Keywords:

Computer Vision, Machine Perception, Scientific Discovery

Abstract

In our technology-dependent modern world, it is imperative to monitor the Sun for space weather threats to critical infrastructure. Topological data analysis (TDA) is a new set of mathematical techniques used in data analysis and machine learning. We demonstrate that TDA can robustly detect and classify solar surface and coronal activity. This technique is a promising step toward future application in predictive space weather modeling.
AAAI-23 Proceedings Cover

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Published

2023-09-06

How to Cite

Lytle, A., Pritchard, N., Aarnio, A., & Weighill, T. (2023). Toplogical Data Analysis Detects and Classifies Sunspots (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16274-16275. https://doi.org/10.1609/aaai.v37i13.26997

Issue

Vol. 37 No. 13: AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program