2025/12/17 by Tony Menzo, Alexander Roman, Menzo, Tony +13 · 1 voice · 7 citations
Computer Science · Decision Sciences · Social Sciences · #Agency (philosophy) #Artificial Intelligence in Law #Construct (python library) #Event (particle physics) #Interface (matter) #Multi-Agent Systems and Negotiation #Orchestration #Pipeline (software) #Scientific Computing and Data Management #Software deployment #Workflow #hep-ex #hep-ph
paper · pdf · doi:10.48550/arxiv.2512.15867
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/12/17 · openalex created_date 2025/12/21 · openalex updated_date 2026/08/05
Many theoretical and experimental workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to integrate external LLMs into general HEP workflows spanning theoretical calculations, simulation, and data analysis. The framework enables LLMs to interface with domain-specific tools and to construct and manage diverse HEP pipelines while preserving transparency, reproducibility, and human oversight. To demonstrate these capabilities, we present a representative case study in the context of a Beyond the Standard Model (BSM) Monte Carlo signal validation that spans model generation, event simulation, and analysis within an established, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for human-in-the-loop, agent-assisted workflows across high-energy physics.