TL;DR
MadAgents is a set of intelligent agents integrated with MadGraph that simplifies and automates complex particle physics simulations, enhancing user support and research efficiency.
Contribution
Introducing MadAgents, a novel agent-based system that automates and improves particle physics simulations with self-learning capabilities.
Findings
MadAgents effectively support diverse simulation tasks.
They automate event generation and autonomous campaigns.
The system includes a self-improvement loop for continuous enhancement.
Abstract
We uncover an effective and communicative set of agents working with MadGraph. Agentic installation, learning-by-doing training, and user support provide easy access to state-of-the-art simulations and accelerate LHC research. We show in detail how MadAgents interact with inexperienced and advanced users, support a range of simulation tasks, and analyze results. In a second step, we illustrate how MadAgents automatize event generation and run an autonomous simulation campaign, starting from a pdf file of a paper. The updated Claude Code implementation includes a self-improvement loop.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.