AI 中文总结
AtomWorld-Mirror是面向原子系统关键演化主干的时间感知宏步世界模型，可将原子模拟加速10³至10⁴倍，同时保留结构有效性与时间语义。
AI 中文摘要
原子模拟是研究长期材料演化的基础工具，涵盖扩散、缺陷动力学、界面反应及断裂等过程。然而，传统模拟器通常以微观分辨率推进，在达到具有结构重要性的状态前，会在低影响的局部更新上消耗大量计算，形成演化分辨率瓶颈，限制了长时程模拟。我们提出AtomWorld-Mirror，一种面向原子系统关键演化主干的时间感知宏步世界模型。对于分步原子模拟，AtomWorld-Mirror将短微事件片段提炼为关键状态间的物理可达跃迁，通过潜在宏步动力学联合预测稀疏结构编辑与累积物理时间。每个跃迁受局部可达性、存量守恒及连续时间一致性约束。通过将局部原子物理摊销为可复用的潜在宏模型，并以宏步推理替代显式微事件重放，该方案为大幅加速长期材料演化预测提供了途径，同时保留结构有效性与时间语义。在五个原子系统（包括富Cu反应堆压力容器钢辐照老化、Cu-Zr金属玻璃及Li₃N基反钙钛矿固体电解质）上，宏步推理相比逐事件模拟实现了10³至10⁴倍的加速。
英文摘要
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.
CommentsProject page: https://atomworld-mirror.github.io
