Speaker
Description
The Jost function plays a central role in quantum few-body problems by providing direct access to the partial-wave S-matrix and its bound-state pole residues. These residues are related to nuclear vertex constants (NVCs) and asymptotic normalization constants (ANCs), which govern the asymptotic behavior of bound-state wave functions and the strength of reaction amplitudes. In this talk, I will present a physics-informed neural network (PINN) framework to determine bound states by exploiting the Hermitian structure of the bound-state Hamiltonian. I will then quantify uncertainties in the bound-state energies and demonstrate how the resulting bound-state wave functions can be used to construct the Jost function. As a benchmark, we will reconstruct the bound-state wave function generated by a Gaussian potential to assess the accuracy of the approach.