Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification

arXiv:2404.10757v1 Announce Type: cross
Abstract: Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processed to extract astronomical patterns and information. In this study, we present a comprehensive evaluation of deep-learning and large language model (LLM) based models for the automatic classification of variable star light curves, based on large datasets from the Kepler and K2 missions. Special emphasis is placed on Cepheids, …

abstract advancement arxiv astro-ph.im astro-ph.sr classification cs.cl cs.lg deep learning evaluation evolution extract information light llm machine machine learning machine learning techniques patterns serve study type