Deep neural network for fitting analytical potential energy curve of diatomic molecules from ro-vibrational spectra

We present a new approach which employs a deep neural network to obtain parameters of analytical representation of potential energy curve of diatomic molecule. We test the approach to find spectroscopic characteristics for the ground X²Sigma⁺ electronic state of MgF molecule based on the experimental energies of ro-vibrational transitions. The result shows that a deep neural network can be applied in characterisation of interatomic potential of diatomic molecule. Our approach is competitive with those obtained using other methods tested, i.e. shallow neural network and the socalled brute force method.