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arXiv · 2605.10115

Generating Symmetric Materials using Latent Flow Matching

Anmar Karmush·Cedric Mathieu Brandenburg·Soheil Ershadrad·Johanna Rosén·Michael Felsberg·Filip Ekström Kelvinius
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Abstract

Tackling the task of materials generation, we aim to enhance the previously proposed All-atom Diffusion Transformer (ADiT) by introducing SymADiT, a symmetry-aware variant. To do so, we use a representation of materials based on Wyckoff positions. We follow ADiT and perform generative modelling in latent space, adapted to our symmetry-aware representation. By forcing the output of the generative model to adhere to the symmetry restrictions imposed by the generated crystal's space group and each atom's Wyckoff-position, the generated materials exhibit more realistic symmetry properties. We benchmark our method against both symmetry-aware and symmetry-agnostic models for materials generation and show competitive performance, generating stable, symmetric materials with a simple Transformer architecture.

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Anmar Karmush, Cedric Mathieu Brandenburg, Soheil Ershadrad, Johanna Rosén, Michael Felsberg, Filip Ekström Kelvinius. 2026-05-11. Generating Symmetric Materials using Latent Flow Matching. https://arxiv.org/abs/2605.10115

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