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Astro-MoE: Mixture of Experts for Multiband Astronomical Time Series

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arxiv 2507.12611 v1 pith:CNMOB6NE submitted 2025-07-16 astro-ph.IM

Astro-MoE: Mixture of Experts for Multiband Astronomical Time Series

classification astro-ph.IM
keywords astro-moeastronomicalbandsexpertsmixturemodelmultibandseries
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Multiband astronomical time series exhibit heterogeneous variability patterns, sampling cadences, and signal characteristics across bands. Standard transformers apply shared parameters to all bands, potentially limiting their ability to model this rich structure. In this work, we introduce Astro-MoE, a foundational transformer architecture that enables dynamic processing via a Mixture of Experts module. We validate our model on both simulated (ELAsTiCC-1) and real-world datasets (Pan-STARRS1).

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

    astro-ph.IM 2026-06 unverdicted novelty 5.0

    ORACLE-2 multimodal classifiers raise macro F1 from 0.52-0.66 (light-curve only) to 0.73 on ZTF Bright Transient Survey data and reach 0.88 on simulated ELAsTiCC data.