{
  "abstract": "Atomistic simulation is a fundamental tool for studying long-term materials evolution, from diffusion and defect dynamics to interfacial reactions and fracture. Yet conventional simulators typically advance at microscopic resolution, spending substantial computation on low-impact local updates before reaching structurally consequential states, an evolutionary-resolution bottleneck that limits long-horizon simulation. We propose AtomWorld-Mirror, a time-aware macro-step world model for the critical evolution backbone of atomic systems. For Step-Wise atomistic simulation, AtomWorld-Mirror distills short micro-event segments into physically reachable transitions between key states, jointly predicting sparse structural edits and accumulated physical time through latent macro-step dynamics. Local reachability, inventory conservation, and continuous-time consistency constrain each transition. By amortizing local atomic physics into a reusable latent macro model and replacing explicit micro-event replay with macro-step inference, this formulation provides a path toward substantially faster prediction of long-term materials evolution while preserving structural validity and time semantics. Across five atomic systems, spanning Cu-rich RPV steel irradiation aging, Cu-Zr metallic glass, and Li$_3$N-based anti-perovskite solid electrolyte, macro-step inference delivers a speed up of $10^3$ to $10^4$ times over event-by-event simulation.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.11527",
  "author_total": 10,
  "authors": [
    {
      "name": "Ziming Pan"
    },
    {
      "name": "Ruge Zhang"
    },
    {
      "name": "Haozhi Han"
    },
    {
      "name": "Junkai Zhou"
    },
    {
      "name": "Xingyuan Chen"
    },
    {
      "name": "Yifeng Chen"
    },
    {
      "name": "Yunquan Zhang"
    },
    {
      "name": "Ting Cao"
    },
    {
      "name": "Yunxin Liu"
    },
    {
      "name": "Kun Li"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7fqpncdg5gv5h.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.11527",
  "fulltext_url": null,
  "id": "7fqpncdg5gv5h",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.11527",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ],
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "openalex",
      "2505|Machine Learning in Materials Science"
    ]
  ],
  "openalex": "W7221108650",
  "pdf_url": "https://arxiv.org/pdf/2610.11527",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7fqpncdg5gv5h.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:06Z",
      "native_id": "2610.11527",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.11527"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.mtrl-sci",
      "subfield": "condensed-matter"
    }
  ],
  "title": "AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics",
  "title_text": "AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:06Z",
  "url": "https://research.draconitic.com/paper/7fqpncdg5gv5h",
  "venue": "arXiv",
  "versions": []
}