Problem
Research questions and friction points this paper is trying to address.
exoplanet research
transmission spectroscopy
atmospheric characterization
Bayesian retrieval
workflow integration
ASTER -- Agentic Science Toolkit for Exoplanet Research
🤖 AI Summary
This work addresses the complexity and heavy reliance on expert knowledge in multi-step, cross-tool workflows for exoplanet atmospheric characterization by proposing the first large language model–based intelligent agent framework. The framework integrates the NASA Exoplanet Archive API, the TauREx radiative transfer model, and Bayesian retrieval tools, orchestrating an end-to-end automated pipeline—from data acquisition and synthetic spectrum generation to atmospheric parameter inference—through structured prompting and workflow coordination. Equipped with tool-calling and iterative reasoning capabilities, the agent efficiently processes multiple observational datasets, as demonstrated in a comprehensive atmospheric retrieval for WASP-39b. This successful application validates the framework’s feasibility and practical utility, establishing a novel intelligent paradigm for astronomical data analysis.
📝 Abstract
The expansion of exoplanet observations has created a need for flexible, accessible, and user-friendly workflows. Transmission spectroscopy has become a key technique for probing atmospheric composition of transiting exoplanets. The analyses of these data require the combination of archival queries, literature search, the use of radiative transfer models, and Bayesian retrieval frameworks, each demanding specialized expertise. Modern large language models enable the coordinated execution of complex, multi-step tasks by AI agents with tool integration, structured prompts, and iterative reasoning. In this study we present ASTER, an Agentic Science Toolkit for Exoplanet Research. ASTER is an orchestration framework that brings LLM capability to the exoplanetary community by enabling LLM-driven interaction with integrated domain-specific tools, workflow planning and management, and support for common data analysis tasks. Currently ASTER incorporates tools for downloading planetary parameters and observational datasets from the NASA Exoplanet Archive, as well as the generation of transit spectra from the TauREx radiative transfer model, and the completion of Bayesian retrieval of planetary parameters with TauREx. Beyond tool integration, the agent assists users by proposing alternative modeling approaches, reporting potential issues and suggesting solutions, and interpretations. We demonstrate ASTER's workflow through a complete case study of WASP-39b, performing multiple retrievals using observational data available on the archive. The agent efficiently transitions between datasets, generates appropriate forward model spectra and performs retrievals. ASTER provides a unified platform for the characterization of exoplanet atmospheres. Ongoing development and community contributions will continue expanding ASTER's capabilities toward broader applications in exoplanet research.
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI agent
large language model
exoplanet atmosphere
Bayesian retrieval
workflow orchestration
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