Abstract
I will present a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert spaces. While broadly applicable to diverse quantum systems-including atoms and molecules-the talk will focus on the photoabsorption cross section of light nuclei, for which benchmarks against numerically exact methods are available. Our theoretical predictions are accompanied by robust uncertainty quantification, enabling meaningful comparisons with experiments.
