Multi-Agent System for Cosmological Parameter Analysis

arXiv (Cornell University)

Abstract

Multi-agent systems (MAS) utilizing multiple Large Language Model agents with Retrieval Augmented Generation and that can execute code locally may become beneficial in cosmological data analysis. Here, we illustrate a first small step towards AI-assisted analyses and a glimpse of the potential of MAS to automate and optimize scientific workflows in Cosmology. The system architecture of our example package, that builds upon the autogen/ag2 framework, can be applied to MAS in any area of quantitative scientific research. The particular task we apply our methods to is the cosmological parameter analysis of the Atacama Cosmology Telescope lensing power spectrum likelihood using Monte Carlo Markov Chains. Our work-in-progress code is open source and available at https://github.com/CMBAgents/cmbagent.

Authors 7

1. Kristen M. Surrao

   Columbia University

   Affiliation as printed

   Columbia University

2. Íñigo Zubeldía

   University of Cambridge

   Affiliation as printed

   University of Cambridge

3. Boris Bolliet

   University of Cambridge

   Affiliation as printed

   University of Cambridge

4. Miles Cranmer

   University of Cambridge

   Affiliation as printed

   University of Cambridge

5. Antony Lewis

   University of Sussex

   Affiliation as printed

   University of Sussex

6. Blake D. Sherwin

   University of Cambridge

   Affiliation as printed

   University of Cambridge

7. Julien Lesgourgues Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University