A neural network approach for solution of the schrödinger equation for a particle in the pöschl–teller potential

We use a shallow artificial neural network (ANN) to solve the Schrödinger equation and find the ground state energy and wavefunction for a particle in the Pöschl–Teller potential. We also use the finite difference method (FDM) to find these quantities and compare the results obtained using the two methods with the analytical results. Results obtained using the neural network are in good agreement with the analytical results. Our work reaffirms the promising nature of application of artificial neural networks in quantum mechanics.