… We present the notion of quantum-assisted greedy algorithms (QAGA) to improve the fidelity
of the near-term QAs. Algorithm 1 illustrates the QAGA process. Let z∗ be the ground state …

… Here, we propose a greedy algorithm that generates routes by using information from all …
Quantum-assisted solution paths for the capacitated vehicle routing problem. In 2023 IEEE …

… quantum-assisted algorithm, namely the Non-dominated Quantum Optimization algorithm
(… NDQO algorithm to the state-of-theart evolutionary algorithms, demonstrating that the NDQO …

… A main difference between the quantum-enhanced greedy algorithm that we develop and
prior iterative approaches is its robustness to noise, which is key when executing quantum …

… very naturally is a genetic algorithm; to hybridize a genetic algorithm with quantum annealing
in … algorithm. We refer to such a genetic algorithm as a quantum-assisted genetic algorithm …

… as greedy selection \((… quantum assisted routines we find solutions which increase the
quality of predictive model output while reducing the input dimensionality to the learning algorithm …

… our quantum-assisted … quantum assisted routines we find solutions which increase the
quality of predictive model output while reducing the input dimensionality to the learning algorithm …

… To tackle the complex optimization in our formulated entanglement distribution problem, we
now leverage recent advanced QC [7], [13]–[19] to design two quantum-assisted algorithms. …

… The quantum assisted eigensolver and iterative quantum assisted eigensolver (IQAE)
demonstrate a systematic structure in their algorithm [25, 26]. Their classical optimization program …

… In this paper we have successfully demonstrated a quantum-assisted algorithm to solve
the Fleet Conversion problem. This shows firstly the advantage of having an algorithm that …