… quantum stochastic optimization reported here): for example, we can call a local optimization
procedure every tloc quantum … performs better than quantum stochastic optimization: it finds…

… In this Review, we aim to give an overview of quantum optimization. … quantum advantage
is possible in each context. Then, we outline the core building blocks for quantum optimization …

… Quantum annealing employs quantum fluctuations in frustrated systems or … the quantum
fluctuation down to zero eventually. Often this can be more effective in multivariable optimization …

… required by the quantum computers. It uncovers the capability of quantum computers that
can impact our lives in various viewpoints like cyber security, traffic optimization, medicines, …

… breakthroughs in the development of quantum domain firstly, then summarizes the existing
quantum algorithms from two aspects: quantum optimization and quantum learning. After that, …

… our gradient computation procedure for quantum optimization problems is the need to … in
quantum optimization procedures) and a phase oracle (which is common in quantum algorithms…

… of the theoretical motivations for QA as a heuristic quantum optimization algorithm, the
software and hardware that is required to use such quantum processors, and the state-of-the-art …

… of the optimization method. Finally, this study introduces quasi-Newton optimization methods
in … and presents quantitative results for the Quantum Approximate Optimization Algorithm. …

… Figure 1.1: Illustration of the quantum machine learning design methodology: A parameterized
quantum circuit with a pre-specified architecture is optimized via its vector of parameters, θ…

… After a brief discussion of the prospects of solving classical optimization problems with
near-term quantum devices in section 5, we elaborate on the choice of suitable optimizers for the …