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 …

In this short review article, we aim to provide physicists not working within the quantum
computing community a hopefully easy-to-read introduction to the state of the art in the field …

Realizing quantum speedup for practically relevant, computationally hard problems is a
central challenge in quantum information science. Using Rydberg atom arrays with up to …

Shortcuts to adiabaticity (STA) are fast routes to the final results of slow, adiabatic changes
of the controlling parameters of a system. The shortcuts are designed by a set of analytical …

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

Hybrid quantum-classical algorithms are central to much of the current research in quantum
computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era …

Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …

We discuss how quantum computation can be applied to financial problems, providing an
overview of current approaches and potential prospects. We review quantum optimization …

Many quantum algorithms have daunting resource requirements when compared to what is
available today. To address this discrepancy, a quantum-classical hybrid optimization …

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 …