Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …

Experiments on disordered alloys,–suggest that spin glasses can be brought into low-
energy states faster by annealing quantum fluctuations than by conventional thermal …

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

Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …

Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

Faster algorithms for combinatorial optimization could prove transformative for diverse areas
such as logistics, finance and machine learning. Accordingly, the possibility of quantum …

Superconducting qubits are leading candidates in the race to build a quantum computer
capable of realizing computations beyond the reach of modern supercomputers. The …

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical
variational algorithm designed to tackle combinatorial optimization problems. Despite its …

In recent years, there has been a rising interest in high‐dimensional quantum states and
their impact on quantum communication. Indeed, the availability of an enlarged Hilbert …