Iterative optimization of hard spin glass problems with high frequency AC drives (Part I)

Performance improvements of quantum algorithms such as quantum annealing, adiabatic quantum computing and the quantum approximate optimization algorithm over smart classical algorithms are often marginal, particularly when concerns such as the overhead of computing quantum expectation values for variational circuits, and the immense prefactor disadvantages quantum hardware exhibits compared to parallel silicon, are taken into account. In light of these challenges, we introduce a new quantum algorithm called IST-SAT (Iterative-Symphonic Tunneling-Boolean Satisfiability Problem) which circumvents computing gradients and parameter optimization. IST-SAT is a novel heuristic update to high-depth QAOA that simulates evolution under high-frequency drives tuned to the problem graph, and iteratively updates the applied Hamiltonian using bitstrings from previous shots. In this first talk, we introduce the IST-SAT algorithm and sketch its mechanism and workflow.