Ising machines are hardware solvers that aim to find the absolute or approximate ground
states of the Ising model. The Ising model is of fundamental computational interest because …

Practical challenges in simulating quantum systems on classical computers have been
widely recognized in the quantum physics and quantum chemistry communities over the …

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

With rapid recent advances in quantum technology, we are close to the threshold of
quantum devices whose computational powers can exceed those of classical …

Quantum Machine Learning bridges the gap between abstract developments in quantum
computing and the applied research on machine learning. Paring down the complexity of the …

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

Shortcuts to adiabaticity provide fast protocols for quantum state preparation in which the
use of auxiliary counterdiabatic controls circumvents the requirement of slow driving in …

One of the main applications of future quantum computers will be the simulation of quantum
models. While the evolution of a quantum state under a Hamiltonian is straightforward (if …

We develop from first principles Markovian master equations suited for studying the time
evolution of a system evolving adiabatically while coupled weakly to a thermal bath. We …

We show that the NP-hard quadratic unconstrained binary optimization (QUBO) problem on
a graph G can be solved using an adiabatic quantum computer that implements an Ising …