Randomized Benchmarking of Local Zeroth-Order Optimizers for Variational
  Quantum Systems
Lucas Tecot Cho-Jui Hsieh
In the field of quantum information, classical optimizers play an important
role. From experimentalists optimizing their physical devices to theorists
exploring variational quantum algorithms, many aspects of quantum information
require the use of a classical optimizer. For this reason, there are many
papers that benchmark the effectiveness of different optimizers for specific
quantum optimization tasks and choices of parameterized algorithms. However,
for researchers exploring new algorithms or physical devices, the insights from
these studies don't necessarily translate. To address this concern, we compare
the performance of classical optimizers across a series of partially-randomized
tasks to more broadly sample the space of quantum optimization problems. We
focus on local zeroth-order optimizers due to their generally favorable
performance and query-efficiency on quantum systems. We discuss insights from
these experiments that can help motivate future works to improve these
optimizers for use on quantum systems.