AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics

2026-10-08

AI Summary

This study addresses the computational bottleneck in long-term atomic simulations caused by microscopic resolution. We propose a time-aware macro-stepping world model that constructs a latent macro-dynamics framework, distilling microscopic events into physically reachable transitions between key states. The method incorporates local reachability, inventory conservation, and continuous-time consistency constraints, while integrating latent macro-step reasoning with sparse structural editing prediction. Experimental results demonstrate that this approach achieves $10^3$- to $10^4$-fold acceleration over event-by-event simulations across diverse material systems, offering an efficient new paradigm for cross-scale atomic simulation.

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.

Problem

• atomistic simulation
• materials dynamics
• long-term evolution
• resolution bottleneck
• macro-step modeling

Innovation

• macro-step world model
• atomistic simulation
• latent dynamics
• materials evolution
• time-aware distillation