physics.optics · 2026-06-18 · No. 27

Optics, 2026-06-18.

1 new papers in physics.optics. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening

    Kasper Helverskov Petersen, François R J Cornet, Martin Ovesen, Mikkel Jordahn, Kristian S. Thygesen, Mikkel N. Schmidt

    physics.optics · cond-mat.mtrl-sci · cs.AI

    Scalable prediction of optical spectra is a critical component of high-throughput materials screening for optoelectronic applications such as solar cells. Existing surrogate models are trained on spectra computed from lower levels of theory or rely on rotation-invariant scalar features, limiting their geometric expressiveness. We explore the use of equivariant graph neural networks for optical spectra prediction, adapting GotenNet to this...

    arxiv.org/abs/2606.19133 · PDF

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