During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …

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 …

Parameterized quantum circuits (PQCs) have been widely used as a machine learning
model to explore the potential of achieving quantum advantages for various tasks. However …

Quantum computing offers new heuristics for combinatorial problems. With small-and
intermediate-scale quantum devices becoming available, it is possible to implement and test …

Variational quantum algorithms (VQAs) represent a promising approach to utilizing current
quantum computing infrastructures. VQAs are based on a parameterized quantum circuit …

Abstract The Quantum Alternating Operator Ansatz (QAOA+) is an extension of the Quantum
Approximate Optimization Algorithm (QAOA), where the search space is smaller in solving …

Variational quantum algorithms (VQAs) represent a promising approach to utilizing current
quantum computing infrastructures. VQAs are based on a parameterized quantum circuit …

Motivated by recent progress in quantum hardware and algorithms researchers have
developed quantum heuristics for optimization problems, aiming for advantages over …

Integer programming (IP), as the name suggests is an integer-variable-based approach
commonly used to formulate real-world optimization problems with constraints. Currently …

The set partitioning problem and its decision variant (ie, the exact cover problem) are
combinatorial optimization problems that were historically crucial in the quantum …