A neural operator framework for data-driven discovery of stability and receptivity in physical systems

Chengyun Wang, Liwei Chen, Nils Thuerey

Open source

DOI: 10.1073/pnas.2526451123
Published: 2026-10-16
Container: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1073/pnas.2526451123,
  title = {A neural operator framework for data-driven discovery of stability and receptivity in physical systems},
  author = {Chengyun Wang and Liwei Chen and Nils Thuerey},
  year = {2026},
  journal = {Proceedings of the National Academy of Sciences},
  doi = {10.1073/pnas.2526451123},
  url = {https://doi.org/10.1073/pnas.2526451123}
}

RIS

TY  - JOUR
TI  - A neural operator framework for data-driven discovery of stability and receptivity in physical systems
AU  - Chengyun Wang
AU  - Liwei Chen
AU  - Nils Thuerey
PY  - 2026
JO  - Proceedings of the National Academy of Sciences
DO  - 10.1073/pnas.2526451123
UR  - https://doi.org/10.1073/pnas.2526451123
ER  -

APA

Wang, C., Chen, L., & Thuerey, N. (2026). A neural operator framework for data-driven discovery of stability and receptivity in physical systems. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2526451123

Source records

crossref · retrieved 2026-11-07T22:22:11.859Z