Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …

Abstract Variational Quantum Algorithms (VQAs) have received considerable attention due
to their potential for achieving near-term quantum advantage. However, more work is …

Hybrid quantum-classical algorithms are central to much of the current research in quantum
computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era …

Variational hybrid quantum-classical algorithms (VHQCAs) are near-term algorithms that
leverage classical optimization to minimize a cost function, which is efficiently evaluated on …

The determination of vehicle routes fulfilling connectivity, time, and operational constraints is
a well-studied combinatorial optimization problem. The NP-hard complexity of vehicle …

The quantum approximate optimization algorithm (QAOA) is a hybrid variational quantum-
classical algorithm that solves combinatorial optimization problems. While there is evidence …

The quantum approximate optimization algorithm (QAOA) generates an approximate
solution to combinatorial optimization problems using a variational ansatz circuit defined by …

Realizing the potential of near-term quantum computers to solve industry-relevant
constrained-optimization problems is a promising path to quantum advantage. In this work …