Learning to optimize variational quantum circuits to solve combinatorial problems
Quantum computing is a computational paradigm with the potential to outperform classical
methods for a variety of problems. Proposed recently, the Quantum Approximate …
methods for a variety of problems. Proposed recently, the Quantum Approximate …
Multistart methods for quantum approximate optimization
Hybrid quantum-classical algorithms such as the quantum approximate optimization
algorithm (QAOA) are considered one of the most promising approaches for leveraging near …
algorithm (QAOA) are considered one of the most promising approaches for leveraging near …
Network community detection on small quantum computers
In recent years, a number of quantum computing devices with small numbers of qubits have
become available. A hybrid quantum local search (QLS) approach that combines a classical …
become available. A hybrid quantum local search (QLS) approach that combines a classical …
Reinforcement-learning-based variational quantum circuits optimization for combinatorial problems
Quantum computing exploits basic quantum phenomena such as state superposition and
entanglement to perform computations. The Quantum Approximate Optimization Algorithm …
entanglement to perform computations. The Quantum Approximate Optimization Algorithm …
Quantum Optimization Algorithms in Operations Research: Methods, Applications, and Implications
F Klug - arxiv preprint arxiv:2312.13636, 2023 - arxiv.org
Quantum optimization algorithms (QOAs) have the potential to fundamentally transform the
application of optimization methods in decision making. For certain classes of optimization …
application of optimization methods in decision making. For certain classes of optimization …