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Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

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 f...

AuthorsVan Khoa Nguyen, Alexandros Kalousis
Primary categorycs.LG
Published13 August 2026
Last updated at source13 August 2026
cs.LG
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