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Finding symmetry breaking order parameters with Euclidean neural networks
Curie's principle states that “when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them.” We demonstrate that symmetry equivariant neural networks uphold Curie's principle and can be used to articulate many symmetry-relevant scientific question...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1103/PhysRevResearch.3.L012002 http://cds.cern.ch/record/2750640 |