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 …

Abstract Machine learning has achieved dramatic success in a broad spectrum of
applications. Its interplay with quantum physics may lead to unprecedented perspectives for …

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

The recent success in quantum annealing, ie, optimization of the cost or energy functions of
complex systems utilizing quantum fluctuations is reviewed here. The concept is introduced …

We review here some recent work in the field of quantum annealing, alias adiabatic
quantum computation. The idea of quantum annealing is to perform optimization by a …

Quantum annealing is a generic name of quantum algorithms that use quantum-mechanical
fluctuations to search for the solution of an optimization problem. It shares the basic idea …

The reconstruction of charged particles will be a key computing challenge for the high-
luminosity Large Hadron Collider (HL-LHC) where increased data rates lead to a large …

Recent developments in quantum annealing techniques have been indicating potential
advantage of quantum annealing for solving NP-hard optimization problems. In this article …

In this article, we show how to map a sampling of the hardest artificial intelligence problems
in space exploration onto equivalent Ising models that then can be attacked using quantum …

We introduce a class of dissipative quantum spin models with local interactions and without
quenched disorder that show glassy behavior. These models are the quantum analogs of …