SciPost Submission Page
HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency
by Tony Menzo, Alexander Roman, Sergei Gleyzer, Konstantin Matchev, George T. Fleming, Stefan Hoche, Stephen Mrenna, Prasanth Shyamsundar
Submission summary
| Authors (as registered SciPost users): | Tony Menzo |
| Submission information | |
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| Preprint Link: | scipost_202601_00065v1 (pdf) |
| Code repository: | https://github.com/tonymenzo/heptapod |
| Code version: | v1.0 |
| Code license: | GPL-3.0 |
| Date submitted: | Jan. 27, 2026, 10:04 p.m. |
| Submitted by: | Tony Menzo |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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| Approach: | Computational |
The author(s) disclose that the following generative AI tools have been used in the preparation of this submission:
Claude (Anthropic; accessed December 2025) was used to assist with limited menial programming-related tasks. ChatGPT (OpenAI; accessed December 2025) was used minimally for proofreading and stylistic review of non-technical text. All scientific content and conclusions were developed by the authors.
Abstract
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 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.