https://doi.org/10.1140/epjb/s10051-021-00261-1
Regular Article - Computational Methods
Machine learning S-wave scattering phase shifts bypassing the radial Schrödinger equation
1
, Berlin, Germany
2
Departament de Física de la Matèria Condensada, Universitat de Barcelona, Carrer Martí i Franquès 1, 08028, Barcelona, Spain
3
National Institute of Chemical Physics and Biophysics, Rävala 10, 10143, Tallinn, Estonia
Received:
3
August
2021
Accepted:
8
December
2021
Published online:
26
December
2021
We present a proof of concept machine learning model resting on a convolutional neural network capable of yielding accurate scattering s-wave phase shifts caused by different three-dimensional spherically symmetric potentials at fixed collision energy thereby bypassing the radial Schrödinger equation. In our work, we discuss how the Hamiltonian can serve as a guiding principle in the construction of a physically-motivated descriptor. The good performance, even in presence of bound states in the data sets, exhibited by our model that accordingly is trained on the Hamiltonian through each scattering potential, demonstrates the feasibility of this proof of principle.
© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2021
