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arxiv: 2606.31214 · v1 · pith:OENXX7VFnew · submitted 2026-06-30 · ✦ hep-ph

EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics

Yang Xiao , Yuanfang Yue , Yang Zhang This is my paper

Pith reviewed 2026-07-01 05:11 UTC · model grok-4.3

classification ✦ hep-ph
keywords parameter scanshigh-energy physicsAI agentsconfiguration files.ini formatcomputational workflowsreproducibility
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The pith

EasyScan_HEP 2 adds command-line and machine-readable interfaces so AI assistants can turn natural language requests into complete parameter scan .ini files.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper upgrades EasyScan_HEP so that AI agents can prepare and steer computational workflows for high-energy physics parameter scans. It exposes new interfaces that let an assistant read a user's request in ordinary language and output an explicit .ini file that names the scan method, the external programs to run, the constraints, and the desired outputs. The resulting file remains inspectable by the user through a local web interface. The upgrade also lets AI help add new scan methods to the framework while the overall process stays reproducible and under user control.

Core claim

EasyScan_HEP 2 exposes agent-facing command-line and machine-readable interfaces, allowing an assistant to translate natural language requests into an explicit .ini configuration that defines the scan method, external-program workflow, constraints, and outputs. The framework also supports AI-assisted extension to new scan methods, as illustrated by the integration of BESTFIT, EMCEE, and DYNESTY, while preserving reproducibility, transparency, and user control.

What carries the argument

Agent-facing command-line and machine-readable interfaces that convert natural language into explicit .ini scan configuration files.

If this is right

  • AI assistants can define scan methods, external-program workflows, constraints, and outputs in a single .ini file.
  • New scan methods such as BESTFIT, EMCEE, and DYNESTY can be added through AI-assisted extension.
  • Generated configurations remain inspectable by users via a local Web UI.
  • Parameter scans become compatible with AI-assisted workflows while keeping reproducibility and user control intact.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Physicists could delegate routine scan setup to agents and focus only on reviewing the final .ini file.
  • The same interface pattern could be applied to other HEP tools that currently require manual configuration files.
  • Iterative refinement becomes possible if an agent can read the output of one scan and propose an updated .ini for the next run.

Load-bearing premise

AI assistants can produce correct, usable .ini configuration files from natural language descriptions without requiring extensive human debugging or post-processing.

What would settle it

Give an AI assistant a specific natural language request for a parameter scan with defined constraints and outputs, then check whether the generated .ini file runs the intended workflow without any manual edits.

Figures

Figures reproduced from arXiv: 2606.31214 by Yang Xiao, Yang Zhang, Yuanfang Yue.

Figure 1
Figure 1. Figure 1: Agent-oriented architecture of EasyScan_HEP 2 (created with ChatGPT assistance). 3.2. Dry-run configuration checker Another agent-facing upgrade is the configuration checker. A user or agent can check a configuration file without launching any scan point: easyscan --check config.ini For agent use, the same check can return machine-readable output: easyscan --check config.ini --json It parses the .ini file,… view at source ↗
Figure 2
Figure 2. Figure 2: Example of the local EasyScan_HEP 2 Web UI for configuration editing. 5. New scan methods The configuration-centered design of EasyScan_HEP makes it straightforward to extend the package with new scan methods. A scan method in EasyScan_HEP does not need to define a new way of connecting external physics programs. It only needs to decide how points are proposed in the parameter space. The remaining parts of… view at source ↗
Figure 3
Figure 3. Figure 3: Illustration of the scalar-singlet example in the [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
read the original abstract

AI agents are beginning to reshape the preparation and steering of computational workflows in high-energy physics phenomenology. To accommodate this change, we upgrade EasyScan_HEP to make the construction of parameter-scan configuration files more accessible to AI assistance. EasyScan_HEP 2 exposes agent-facing command-line and machine-readable interfaces, allowing an assistant to translate natural language requests into an explicit .ini configuration that defines the scan method, external-program workflow, constraints, and outputs. The resulting configuration can be inspected through a local Web UI. The framework also supports AI-assisted extension to new scan methods, as illustrated by the integration of BESTFIT, EMCEE, and DYNESTY. In this way, EasyScan_HEP 2 adapts parameter scans to AI-assisted workflows while preserving reproducibility, transparency, and user control.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 1 minor

Summary. The manuscript describes EasyScan_HEP 2, an upgrade to EasyScan_HEP that introduces agent-facing command-line and machine-readable interfaces. These interfaces are intended to allow AI assistants to translate natural language requests into explicit .ini configuration files that define the scan method, external-program workflow, constraints, and outputs. The framework also supports AI-assisted extension to new scan methods (BESTFIT, EMCEE, DYNESTY) and provides a local Web UI for inspection, while preserving reproducibility, transparency, and user control.

Significance. If the claimed interfaces function as described, the work could meaningfully adapt parameter-scan tools to AI-assisted workflows in HEP phenomenology. The emphasis on reproducibility and user control is a constructive feature. However, the absence of any validation for the core AI-translation capability limits the assessed significance of the contribution.

major comments (1)
  1. [Abstract] Abstract: The assertion that the new interfaces 'allow an assistant to translate natural language requests into an explicit .ini configuration' is presented without examples of NL-to-.ini translations, success/failure metrics, integration tests with agents, or usage demonstrations. This claim is load-bearing for the paper's stated purpose yet remains unsubstantiated.
minor comments (1)
  1. The manuscript would benefit from an explicit comparison table or section detailing which features are new in version 2 versus the original EasyScan_HEP.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their thoughtful review and constructive feedback on our manuscript. We address the single major comment below and outline the revisions we will make.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The assertion that the new interfaces 'allow an assistant to translate natural language requests into an explicit .ini configuration' is presented without examples of NL-to-.ini translations, success/failure metrics, integration tests with agents, or usage demonstrations. This claim is load-bearing for the paper's stated purpose yet remains unsubstantiated.

    Authors: We agree that the manuscript would be strengthened by concrete illustrations of the claimed capability. The paper's contribution centers on the design and exposure of agent-facing command-line and machine-readable interfaces that enable an external assistant to produce valid .ini files defining scan methods, workflows, constraints, and outputs. The integration of BESTFIT, EMCEE, and DYNESTY is presented as an example of AI-assisted extension. However, the text does not include explicit NL-to-.ini examples, success metrics, or agent integration tests. In the revised version we will add a short subsection (or appendix) containing (i) representative natural-language prompts, (ii) the corresponding .ini files produced via the new interfaces, and (iii) a brief description of the interaction workflow. This addition will substantiate the abstract claim while preserving the manuscript's focus on framework architecture and reproducibility. We view this as a targeted, low-scope revision that directly responds to the referee's concern. revision: yes

Circularity Check

0 steps flagged

No circularity in software description paper

full rationale

The paper is a software description of EasyScan_HEP 2 upgrades for AI-agent interfaces. It contains no mathematical derivations, equations, fitted quantities, predictions, or self-referential claims. The central assertion is an architectural statement about exposed command-line and machine-readable interfaces; no load-bearing step reduces by construction to its own inputs. No self-citations, uniqueness theorems, or ansatzes are invoked in any derivation chain. This is a normal self-contained software paper with score 0.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a software framework description. No free parameters, mathematical axioms, or invented physical entities are introduced or required.

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discussion (0)

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