Exterior complex scaling enables physics-informed neural networks for quantum scattering
Jin Lei
TL;DR
This work tackles the barrier that oscillatory scattering boundary conditions pose for physics-informed neural networks by marrying exterior complex scaling (ECS) with a driven-equation PINN approach. ECS converts outgoing waves into exponentially decaying functions, allowing a neural network to represent the scattered wave with decaying boundaries while the nuclear interaction remains on the real axis. The method achieves high-accuracy phase shifts and S-matrix elements for nucleon-nucleus scattering ($n+$ $^{40}$Ca at $E_{ ext{lab}}=20$ MeV) and heavy-ion scattering ($^6$Li+$^{208}$Pb at 40 MeV), demonstrating conditions under which PINNs can compete with conventional solvers and enabling differentiable inverse problems. The approach offers a pathway to CMS for multi-channel systems and few-body scattering, where grid-based methods suffer from scaling, by leveraging end-to-end differentiability and a mesh-free representation of the wave function.
Abstract
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving differential equations, yet their application to quantum scattering problems has been hindered by the oscillatory, non-decaying nature of scattering wave functions. In this work, I demonstrate that exterior complex scaling (ECS) transforms scattering boundary conditions into exponentially decaying waves suitable for neural network solutions, enabling PINNs to solve nuclear scattering problems for the first time. I develop a driven-equation formulation where the source term is confined to the real axis, avoiding the need to analytically continue nuclear potentials into the complex plane. The method is validated on nucleon-nucleus scattering (n+$^{40}$Ca at $E_{\text{lab}}=20$~MeV) with 21 partial waves, achieving phase shift accuracy of $Δδ< 0.1^\circ$ for most channels when compared to conventional solvers. I further demonstrate the approach on heavy-ion scattering ($^6$Li+$^{208}$Pb at 40~MeV) with 41 partial waves and strong Coulomb effects. This work establishes the foundation for extending PINNs to inverse problems where end-to-end differentiability enables direct fitting of optical potential parameters, coupled-channel reactions, and few-body scattering where traditional grid methods face exponential scaling.
