Codebase release 2.0 for MadAgents

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 the 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. We also present successive MadAgents updates, including a Claude Code implementation with a self-improvement loop.

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Publication Details

Journal
SciPost Physics Codebases
Published
2026-11-05
DOI
https://doi.org/10.21468/scipostphyscodeb.86-r2.0
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Codebase release 2.0 for MadAgents

Tilman Plehn, Daniel Schiller, Nikita Schmal
SciPost Physics Codebases
Scientific Computing and Data Management
article

Codebase release 2.0 for MadAgents

Tilman Plehn, Daniel Schiller, Nikita Schmal
article en

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 the 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. We also present successive MadAgents updates, including a Claude Code implementation with a self-improvement loop.

SciPost Physics Codebases
Heidelberg University (DE)
Openalex Percentile: Top 14%
Scientific Computing and Data Management
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