Quantum annealers are designed to utilize quantum tunneling to find good solutions to hard
optimization problems. When constructing a family of synthetic inputs to test the potential of a …

The number of topological defects created in a system driven through a quantum phase
transition exhibits a power-law scaling with the driving time. This universal scaling law is the …

We study the performance of the D-Wave 2X quantum annealing machine on systems with
well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass …

We introduce and study the adiabatic dynamics of free-fermion models subject to a local
Lindblad bath and in the presence of a time-dependent Hamiltonian. The merit of these …

Sampling from a Boltzmann distribution is NP-hard and so requires heuristic approaches.
Quantum annealing is one promising candidate. The failure of annealing dynamics to …

Recently, it was demonstrated both theoretically and experimentally on the D-Wave
quantum annealer that transverse-field quantum annealing does not find all ground states …

Genetic algorithms, which mimic evolutionary processes to solve optimization problems, can
be enhanced by using powerful semi-local search algorithms as mutation operators. Here …

Perturbative anticrossings have long been identified as a potential computational bottleneck
for quantum annealing. This bottleneck can appear, for example, when a uniform transverse …

We present multi-qubit correction (MQC) as a novel postprocessing method for quantum
annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set …

Hardware emulation of quantum systems can mimic more efficiently the parallel behaviour of
quantum computations, thus allowing higher processing speed‐up than software …