发表机构
University of Tennessee, Knoxville; McGill University（田纳西大学诺克斯维尔分校; 麦吉尔大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
ASPIRE框架通过Ev-Quiformer等变集合预测器生成鞍点候选并经Dimer优化，在两个铁空位数据集上，较传统Dimer基线提升参考事件覆盖率，同时大幅减少计算时间。
AI 中文摘要
用事件驱动模型预测热激活扩散与缺陷演化，需要识别原子重排机制及其激活势垒。发现相关鞍点是主要计算瓶颈：一个亚稳态可能产生多种重排，而代价高昂的局部搜索可能失败或反复收敛到同一鞍点。为应对这一挑战，我们提出ASPIRE（原子级事件优化鞍点推断框架），该框架从单个初始原子环境预测一组鞍点候选，并通过原始原子间势上的Dimer搜索对其进行优化。该框架的等变集合预测器Ev-Quiformer整合了：（i）几何条件标量-向量事件槽，用于生成多个鞍点提议；（ii）解码器，通过结合原子、槽和锚点相对向量与不变系数，将每个槽映射到完整原子位移场。我们还提供两个数据集：（i）BCCFE4VACAV-4000，包含4000个四空位体心立方铁构型和65450个按初始状态分组的参考事件，用于集合监督和优化后评估；（ii）BCCFE-1TO4VAC，包含5372个各含1至4个空位的构型。理论上，我们确立了提议等变性的条件。实验中，ASPIRE在该基准上实现了77.20%的参考事件覆盖率，而传统Dimer基线为75.73%，同时所需的Dimer力评估数量约为其一半。在50个构型的计时评估中，在所述硬件设置下，ASPIRE将每个构型的挂钟时间从478.8秒减少至176.3秒。
英文摘要
Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their activation barriers. Discovering the associated saddle points is a major computational bottleneck: multiple rearrangements may originate from one metastable state, while costly local searches can fail or repeatedly converge to the same saddle. To address this challenge, we introduce ASPIRE (Atomistic Saddle-Point Inference with Refinement for Events), a framework that predicts a set of saddle candidates from a single initial atomic environment and refines them through Dimer searches on the original interatomic potential. The framework's equivariant set predictor, Ev-Quiformer, integrates (i) geometry-conditioned scalar-vector event slots for generating multiple saddle-point proposals and (ii) a decoder that maps each slot to a full atomic displacement field by combining atom, slot, and anchor-relative vectors with invariant coefficients. We also contribute two datasets: (i) BCCFE4VACAV-4000, comprising 4,000 four-vacancy body-centered cubic iron configurations and 65,450 reference events grouped by initial state for set supervision and post-refinement evaluation; and (ii) BCCFE-1TO4VAC, comprising 5,372 configurations with one to four vacancies each. Theoretically, we establish conditions for proposal equivariance. Experimentally, ASPIRE achieves 77.20% reference-event coverage on this benchmark, compared with 75.73% for a conventional Dimer baseline, while requiring approximately half as many Dimer force evaluations. In a timing evaluation on 50 configurations, ASPIRE reduces wall time per configuration from 478.8 s to 176.3 s under the stated hardware settings.
