# Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties.

@article{Nigam2022EquivariantRF, title={Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties.}, author={Jigyasa Nigam and Michael J. Willatt and M. Ceriotti}, journal={The Journal of chemical physics}, year={2022}, volume={156 1}, pages={ 014115 } }

Symmetry considerations are at the core of the major frameworks used to provide an effective mathematical representation of atomic configurations that is then used in machine-learning models to predict the properties associated with each structure. In most cases, the models rely on a description of atom-centered environments and are suitable to learn atomic properties or global observables that can be decomposed into atomic contributions. Many quantities that are relevant for quantum mechanical…

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