Speaker
Description
In most simulations of nonrelativistic nuclear systems, the wave functions obtained by solving the many-body Schrödinger equation describe the quantum-mechanical amplitudes of nucleonic degrees of freedom only. In these calculations, pionic effects are encoded in nuclear potentials and electroweak currents, where they play a central role in determining the low-momentum behavior of nuclear observables.
In this talk, I will present an alternative quantum Monte Carlo formalism in which relativistic pions and nonrelativistic nucleons are explicitly included in the quantum-mechanical states of the system. Compared with our previous work, we now employ artificial neural networks to represent these amplitudes accurately and efficiently. I will focus primarily on the renormalization of the nucleon mass as a function of the pion momentum cutoff, as well as on the pion-cloud density and momentum distributions. Finally, I will discuss how neural-network quantum states can extend this framework beyond the few-nucleon systems accessible with conventional Green’s function Monte Carlo approaches, paving the way for simulations of larger nuclei.