• Corpus ID: 237491052

Learning reduced order models from data for hyperbolic PDEs

@article{Sarna2021LearningRO,
  title={Learning reduced order models from data for hyperbolic PDEs},
  author={Neeraj Sarna and Peter Benner},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.06156}
}
Given a set of solution snapshots of a hyperbolic PDE, we are interested in learning a reduced order model (ROM). To this end, we propose a novel decompose then learn approach. We decompose the solution by expressing it as a composition of a transformed solution and a de-transformer. Our idea is to learn a ROM for both these objects, which, unlike the solution, are well approximable in a linear reduced space. A ROM for the (untransformed) solution is then recovered via a recomposition. The… 

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