Abstract
We benchmark the 5000+ qubit system Advantage coupled with the Hybrid Solver Service 2 released by D-Wave Systems Inc. in September 2020 by using a new class of optimization problems called garden optimization problems known in companion planting. These problems are scalable to an arbitrarily large number of variables and intuitively find application in real-world scenarios. We derive their QUBO formulation and illustrate their relation to the quadratic assignment problem. We demonstrate that the Advantage system and the new hybrid solver can solve larger problems in less time than their predecessors. However, we also show that the solvers based on the 2000+ qubit system DW2000Q sometimes produce more favourable results if they can solve the problems.
Highlights
The quantum processing units (QPUs) of quantum annealers [1,2,3] have doubled in size almost every two years
We argue that the garden optimization problem is well suited to benchmark quantum annealers since it is scalable to an arbitrary number of variables
We find that the scalability of the garden optimization problem provides the option to benchmark hardware samplers using smaller problem instances as well as hybrid and software solvers by generating larger problem instances
Summary
The quantum processing units (QPUs) of quantum annealers [1,2,3] have doubled in size almost every two years. An input problem for a quantum annealer is typically formulated in terms of a quadratic unconstrained binary optimization (QUBO) problem. We introduce the QUBO formulation of the garden optimization problem. We argue that the garden optimization problem is well suited to benchmark quantum annealers since it is scalable to an arbitrary number of variables. We find that the scalability of the garden optimization problem provides the option to benchmark hardware samplers using smaller problem instances as well as hybrid and software solvers by generating larger problem instances. 2, we introduce the garden optimization problem and formulate it as a QUBO problem suitable as input to quantum annealers.
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