atomistic.Polarizability

class atomistic.Polarizability(*args: Any, **kwargs: Any)

Predicts polarizability tensor using tensor rank factorization. This requires an equivariant representation, e.g. PaiNN, that provides both scalar and vectorial features.

References:

[1]

Schütt, Unke, Gastegger: Equivariant message passing for the prediction of tensorial properties and molecular spectra. ICML 2021, http://proceedings.mlr.press/v139/schutt21a.html

Parameters:

• n_in – input dimension of representation

• n_hidden – size of hidden layers. If an integer, same number of node is used for all hidden layers resulting in a rectangular network. If None, the number of neurons is divided by two after each layer starting n_in resulting in a pyramidal network.

• n_layers – number of layers.

• activation – activation function

• polarizability_key – the key under which the predicted polarizability will be stored