LeWRON is a new agentic framework that automates construction, auditing, and exploration of finite-temperature effective potentials and gravitational-wave predictions for electroweak phase transitions starting from an input Lagrangian.
RooAgent: An LLM Agent for Root-Based High Energy Physics Analysis
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abstract
We present RooAgent as a natural-language interface for Root-based high energy physics data analysis. The package provides physics analysis functions as tools that an LLM agent invokes in response to plain-language prompts. Two operating modes are supported: a LangGraph-based agent compatible with OpenAI's GPT-4.1 via GitHub Copilot and with DeepSeek-V3 via Ollama, and a Model Context Protocol server for use with the Anthropic Claude CLI (Sonnet~4.6). In both modes the analysis logic is implemented in PyRoot and the LLM selects tools and supplies the required arguments. The package supports histogram inspection, event selection, visualisation of kinematic distributions, fitting, and significance estimation, among other tasks. We illustrate RooAgent with tests based on Monte Carlo simulations of $pp\to ZH$ ($Z\to\ell^+\ell^-$, $H\to b\bar{b}$), a multi-task signal-background workflow, a toy statistical analysis, and an application to ATLAS open data for $H\to ZZ^*\to 4\ell$. The package is available on PyPI and the source code is hosted at https://github.com/amanmdesai/RooAgent.
fields
hep-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
An open-source framework that automates BSM Lagrangian construction, anomaly checks, and mass-matrix derivation from natural-language field specifications by using an LLM only as an orchestration layer over a deterministic symbolic backend.
citing papers explorer
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LeWRON: Agentic Analysis of Electroweak Phase Transitions
LeWRON is a new agentic framework that automates construction, auditing, and exploration of finite-temperature effective potentials and gravitational-wave predictions for electroweak phase transitions starting from an input Lagrangian.
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Large Language Model-Assisted Framework for BSM Model Building
An open-source framework that automates BSM Lagrangian construction, anomaly checks, and mass-matrix derivation from natural-language field specifications by using an LLM only as an orchestration layer over a deterministic symbolic backend.