agent/papers/items/2026-2607-04009-physminer-an-agentic-ai-framework-for-discovering-turbulence-physics.md

Paper: PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics

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type: paper title: "PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics" authors: Jiawei Chen, Han Gao, Ping He year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.04009 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-04 updated_at: 2026-07-04 status: queued relevance: high topics:

• agent-evaluation
• memory
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• physics.flu-dyn related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 15 collection_queries: agentic-ai

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agentic-ai
• inferred topics: agent-evaluation, memory, reasoning, tool-use
• arXiv categories: physics.flu-dyn
• collection score: 15

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.04009