Parameter optimization strategies in variational quantum algorithm

A sizeable ongoing research effort focuses on variational quantum algorithms (VQAs), representing leading candidates for computational speed-ups on current quantum devices.

Two major hurdles are the proliferation of low-quality variational local minima and the exponential vanishing of gradients in the cost-function landscape, a phenomenon referred to as barren plateaus.

We present different strategies to address these issues using machine learning and iterative search schemes, showing that these approaches can prepare the ground state of paradigmatic quantum many-body models, circumventing the barren plateau phenomenon.

We discuss the standard features emerging naturally from these different optimization strategies.

Speaker: Dr Glen Bigan Mbeng (University of Innsbruck)

When: 18^th March at 3.30 pm
Where: Aula A “Beppe Nardulli” – Dipartimento Interateneo di Fisica – Bari

More info on Agenda INFN