Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

There are well-developed theoretical tools to analyze how quantum dynamics can solve
computational problems by varying Hamiltonian parameters slowly, near the adiabatic limit …

We benchmark the quantum processing units of the largest quantum annealers to date, the
5000+ qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q …

In this paper I propose a new method of encoding discrete variables into Ising model qubits
for quantum optimisation. The new method is based on the physics of domain walls in one …

Noisy intermediate-scale quantum algorithms require novel paradigms of error mitigation. To
obtain noise-robust quantum computers, each logical qubit is equipped with hundreds or …

We present QuantumSync, the first quantum algorithm for solving a synchronization problem
in the context of computer vision. In particular, we focus on permutation synchronization …

In this work, we introduce a new workflow to solve portfolio optimization problems on
annealing platforms. We combine a classical preprocessing step with a modified …

In this article, we experimentally test the performance of the recently proposed domain-wall
encoding of discrete variables Chancellor, 2019, on Ising model flux qubit quantum …

Quantum annealing is getting increasing attention in combinatorial optimization. The
quantum processing unit by D-Wave is constructed to approximately solve Ising models on …

Leveraging the current generation of quantum devices to solve optimization problems of
practical interest necessitates the development of hybrid quantum-classical (HQC) solution …