EPIMLGFeb 13, 2025

ExoMiner++: Enhanced Transit Classification and a New Vetting Catalog for 2-Minute TESS Data

arXiv:2502.09790v41 citationsh-index: 76Astron J
Originality Incremental advance
AI Analysis

This work addresses the challenge of distinguishing true exoplanet signals from false positives in TESS data for the exoplanet community, representing an incremental improvement over prior methods.

The paper tackles the problem of classifying transit signals in noisy TESS data to identify exoplanet candidates, achieving high accuracy and identifying 7,330 planet candidates from 147,568 unlabeled signals, which helps narrow the search space for follow-up investigations.

We present ExoMiner++, an enhanced deep learning model that builds on the success of ExoMiner to improve transit signal classification in 2-minute TESS data. ExoMiner++ incorporates additional diagnostic inputs, including periodogram, flux trend, difference image, unfolded flux, and spacecraft attitude control data, all of which are crucial for effectively distinguishing transit signals from more challenging sources of false positives. To further enhance performance, we leverage multi-source training by combining high-quality labeled data from the Kepler space telescope with TESS data. This approach mitigates the impact of TESS's noisier and more ambiguous labels. ExoMiner++ achieves high accuracy across various classification and ranking metrics, significantly narrowing the search space for follow-up investigations to confirm new planets. To serve the exoplanet community, we introduce new TESS catalog containing ExoMiner++ classifications and confidence scores for each transit signal. Among the 147,568 unlabeled TCEs, ExoMiner++ identifies 7,330 as planet candidates, with the remainder classified as false positives. These 7,330 planet candidates correspond to 1,868 existing TESS Objects of Interest (TOIs), 69 Community TESS Objects of Interest (CTOIs), and 50 newly introduced CTOIs. 1,797 out of the 2,506 TOIs previously labeled as planet candidates in ExoFOP are classified as planet candidates by ExoMiner++. This reduction in plausible candidates combined with the excellent ranking quality of ExoMiner++ allows the follow-up efforts to be focused on the most likely candidates, increasing the overall planet yield.

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