Diabatic Quantum Annealing for the Frustrated Ring Model

TL;DR

This paper investigates non-adiabatic quantum annealing with optimized schedules for the frustrated ring model, demonstrating potential to avoid exponential slowdowns in system evolution times for up to 39 qubits.

Contribution

It provides numerical evidence that optimized non-adiabatic schedules can bypass exponential scaling in quantum annealing for the frustrated ring model.

Findings

Optimized annealing schedules can avoid exponential slowdown.

Successful scaling up to 39 qubits.

Highlights potential of controllable quantum annealing.

Abstract

Quantum annealing is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable quantum annealing to circumvent bottlenecks associated with the standard implementation of quantum annealing.