Exoplanet Classification Through Vision Transformers with Temporal Image Analysis

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Exoplanet Classification Through Vision Transformers with Temporal Image Analysis

GAFs for exoplanet classification. The upper two frames represent GAFs for “planet” cases, characterized by distinct periodic patterns indicative of planetary transits. The lower two frames show GAFs for “not-planet” candidate cases, which lack the clear periodic structures seen in true exoplanet detections, indicating the absence of exoplanets. — The Astronomical Journal

The classification of exoplanets has been a longstanding challenge in astronomy, requiring significant computational and observational resources.

Traditional methods demand substantial effort, time, and cost, highlighting the need for advanced machine learning techniques to enhance classification efficiency. In this study, we propose a methodology that transforms raw light curve data from NASA’s Kepler mission into Gramian angular fields (GAFs) and recurrence plots (RPs) using the Gramian angular difference field and RP techniques.

These transformed images serve as inputs to the vision transformer (ViT) model, leveraging its ability to capture intricate temporal dependencies. We assess the performance of the model through recall, precision, and F1 score metrics, using a five-fold cross-validation approach to obtain a robust estimate of the model’s performance and reduce evaluation bias.

Our comparative analysis reveals that RPs outperform GAFs, with the ViT model achieving an 89.46% recall and an 85.09% precision rate, demonstrating its significant ability to accurately identify exoplanetary transits. Despite using undersampling techniques to address class imbalance, data set size reduction remains a limitation.

This study underscores the importance of further research into optimizing model architectures to enhance automation, performance, and generalization of the model.

Exoplanet Classification Through Vision Transformers with Temporal Image Analysis, The Astronomical Journal (open access)

Astrobiology,

Explorers Club Fellow, ex-NASA Space Station Payload manager/space biologist, Away Teams, Journalist, Lapsed climber, Synaesthete, Na’Vi-Jedi-Freman-Buddhist-mix, ASL, Devon Island and Everest Base Camp veteran, (he/him) 🖖🏻

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