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 computing is computing beyond classical computing based on quantum
phenomena such as superposition and entanglement. While quantum computing is still …

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

Quantum annealing aims at solving combinatorial optimization problems mapped to Ising
interactions between quantum spins. Here, with the objective of developing a noise-resilient …

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 …

Non-stoquastic Hamiltonians have both positive and negative signs in off-diagonal elements
in their matrix representation in the standard computational basis and thus cannot be …

In solving optimization problems, objective functions generally need to be minimized or
maximized. However, objective functions cannot always be formulated explicitly in a …

Quantum annealing is a generic solver for optimization problems that uses fictitious quantum
fluctuation. The most groundbreaking progress in the research field of quantum annealing is …

We study the role of Hamiltonian complexity in the performance of quantum annealers. We
consider two general classes of annealing Hamiltonians: stoquastic ones, which can be …