In this review, after providing the basic physical concept behind quantum annealing (or
adiabatic quantum computation), we present an overview of some recent theoretical as well …

Adiabatic quantum computing (AQC) started as an approach to solving optimization
problems and has evolved into an important universal alternative to the standard circuit …

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …

The quantum approximate optimization algorithm (QAOA) has proved to be an effective
classical-quantum algorithm serving multiple purposes, from solving combinatorial …

We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and
QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p= 1, 2 rounds is …

We propose digitized-counterdiabatic quantum optimization (DCQO) to achieve polynomial
enhancement over adiabatic quantum optimization for the general Ising spin-glass model …

Recent advance on quantum devices realizes an artificial quantum spin system known as
the D-Wave 2000Q, which implements the Ising model with tunable transverse field. In this …

Among various algorithms designed to exploit the specific properties of quantum computers
with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to …

Classical optimization problems can be solved by adiabatically preparing the ground state of
a quantum Hamiltonian that encodes the problem. The performance of this approach is …

Reverse annealing is a variant of quantum annealing that starts from a given classical
configuration of spins (qubits). In contrast to the conventional formulation, where one starts …