Astronomy2 papers
LLMs in dynamical astronomy
How large language models are transforming astronomical research in celestial mechanics and dynamical astronomy.
ES
Evgeny Smirnov
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Fast, Simple, and Accurate Time Series Analysis with Large Language Models: An Example of Mean-motion Resonances Identification
Evgeny A. Smirnov (2024)
- Published
- May 1, 2024
- Journal
- The Astrophysical Journal · Vol. 966 · No. 2
- DOI
- 10.3847/1538-4357/ad3ae1
At a Glance
LLM can classify resonant behavior without coding or knowledge with high accuracy
Summary
The author created LLM pipeline with just one prompt that classifies resonant arguments and identifies whether time series has libration or circulation. This is a pilot study and simple cases are considered, but the accuracy and F1 score of 100% are remarkable. What's more important: instead of coding and using special methods, it takes 15m to write a prompt and use it.
Method Snapshot
LLM
Background
Basic knowledge of LLMs
Forget about filtering, periodograms, and working with time series. Just use LLMs!
— ES