Space Group Informed Transformer for Crystalline Materials Generation

arXiv:2403.15734v1 Announce Type: cross
Abstract: We introduce CrystalFormer, a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials. The space group symmetry significantly simplifies the crystal space, which is crucial for data and compute efficient generative modeling of crystalline materials. Leveraging the prominent discrete and sequential nature of the Wyckoff positions, CrystalFormer learns to generate crystals by directly predicting the species and locations of symmetry-inequivalent atoms in the unit cell. Our results demonstrate that CrystalFormer matches state-of-the-art …

abstract arxiv autoregressive model compute cond-mat.mtrl-sci cs.lg data generative generative modeling materials modeling nature physics.comp-ph space symmetry transformer type