动态演化晶格对称性，高效生成稳定新颖晶体结构。
DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion
- 通过符号扩散联合建模空间群、原子位置与元素组成。
- 在多个评测中优于现有方法，生成结构松弛后对称性保持良好。
- 适合材料发现、晶体设计领域研究人员快速生成高质量候选结构。
新晶体材料的探索面临巨大的化学成分与结构空间。生成候选材料需同时建模离散的晶格对称性、元素组成与连续几何结构。本文提出DynaCrys，一种晶体生成模型，其空间群通过耦合符号扩散过程与Wyckoff位点占据及元素分布共同演化。空间群变化遵循晶体学中的群-子群关系。当空间群改变时，共享的预训练对称性代码本为合法性约束的随机解码器和对称性约束的晶体几何模型提供统一的Wyckoff词汇表示。在两个独立的弛豫与评估引擎上进行的大规模测试表明，DynaCrys在对称性感知条件下实现最优性能，可发现稳定、唯一且新颖的晶体，尤其在要求弛豫后非平凡对称性的条件下表现突出。该模型还能实现快速采样，生成结构的弛豫诱导位移始终较低。
原文摘要 · Abstract (English)
The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly modeling discrete crystallographic symmetry, elemental composition, and continuous geometry. We introduce DynaCrys, a generative model for crystals in which the space group co-evolves with Wyckoff occupations and elements through a coupled symbolic diffusion process. The structured space-group transitions follow crystallographic group-subgroup relations. As the space group changes, a shared, pretrained symmetry codebook provides both the legality-constrained stochastic decoder and the symmetry-constrained crystal-geometry model with a common representation of the corresponding Wyckoff vocabulary. Across large-scale evaluations using two independent relaxation-and-evaluation engines, DynaCrys achieves best-in-class performance in symmetry-aware discovery of stable, unique, and novel crystals, both overall and under the additional requirement of nontrivial post-relaxation symmetry. It also enables fast sampling while generating structures with consistently low relaxation-induced structural displacements.
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