通过物理对称性破缺机制，实现完整晶体结构的生成。
Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion
- 基于马尔可夫跳跃扩散模型，逆向从低对称性先验生成晶体。
- 在MP20和MPTS-52数据集上显著优于保持对称性的基线方法。
- 适合关注晶体生成与材料设计的科研人员使用。
由于在材料科学中广泛应用，晶体生成近年来受到广泛关注。然而，现有生成模型难以生成完整的晶格参数，限制了其对全局对称性和结构依赖关系的捕捉。当前最先进的方法仅能生成至点阵对称性，并在生成过程中依赖经验分布采样空间群。受物理学中自发对称性破缺的启发，我们提出一种新的基于扩散的框架，通过从最低对称性先验反向生成完整结构规格。该方法利用马尔可夫跳跃扩散过程建模对称性破缺动态，能够以物理合理的方式遍历不同空间群。所提出的模型SbCD（Symmetry-breaking Crystal Diffusion）将跨空间群转换显式纳入生成过程，实现了原理性突破。在MP20和MPTS-52上的首次生成实验表明，SbCD显著优于其对称性保持的基线模型，为晶态材料的生成建模提供了新思路。
原文摘要 · Abstract (English)
Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative models struggle to produce complete crystallographic specifications, limiting their ability to capture global symmetry and structural dependencies. In particular, current state-of-the-art approaches generate crystals only up to site symmetries and rely on sampling space groups from empirical distributions during generation. Inspired by \emph{spontaneous symmetry breaking} in physics, where crystals break symmetries under external conditions, we propose a novel diffusion-based framework that generates full structure specifications by reversing from the lowest-symmetry priors. Our method leverages a Markovian jump-diffusion process to model these symmetry-breaking dynamics, enabling it to traverse different space groups in a physically motivated manner. Our model, dubbed \emph{Symmetry-breaking Crystal Diffusion} (SbCD), introduces a principled approach to explicitly incorporate inter-space-group transitions into the generative process. In de novo generation experiments on MP20 and MPTS-52, SbCD outperforms its symmetry-preserving counterpart by a substantial margin, offering a promising perspective for generative modeling of crystalline materials.
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