Oscillating transverse fields in digital quantum

The RFQA method (Kapit and Oganesyan, arxiv:1710.11056), wherelocal, low-frequency oscillations are added to transverse field terms in adia-batic quantum computing or quantum annealing, can generate polynomialquantum speedups in solving hard optimization problems. Inspired by theperformance of RFQA in continuous time evolution in quantum anneal-ing, we explore a digitized version that could be simulated on universalgate model machines. We apply the digitized version of RFQA to varioustrial problems using classical numerical simulation, and show that RFQAis a potentially promising tool for solving hard problems in optimizationand machine learning.