Speaker
Description
In this talk I will give an introduction to neural network quantum states: a flexible, gauge-symmetry-aware, approach to find the ground state wavefunction of Abelian and non-Abelian lattice gauge theories. I will introduce this method in the context of spin systems, where it was first developed, briefly touching upon some of the applications in condensed matter and quantum chemistry, before covering the works combining this with gauge theories: $Z_2$, $U(1)$, and $SU(2)$. There is an increasing amount of attention paid to tensor network and digital quantum simulation approaches to the Hamiltonian formulation of lattice gauge theories, due in part to the possible access to time evolution and non-equilibrium phenomena. Neural network quantum states, which are also set in this formalism, offer this route to previously hard to access regimes whilst building upon much of the machinery of conventional lattice QCD that has been developed over the past few decades. I will end my talk by drawing attention to the many open-sourced resources in this field, with hopes to lowering the barrier for entry and spark interest in this emerging research area.