Optimization, sampling and machine learning are topics of broad interest that have inspired
significant developments and new approaches in quantum computing. One such approach …

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

Quantum simulation has emerged as a valuable arena for demonstrating and understanding
the capabilities of near-term quantum computers,–. Quantum annealing, has been …

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 …

The transistor celebrated its 75th birthday in 2022. The continued scaling of the transistor
defined by Moore's law continues, albeit at a slower pace. Meanwhile, computing demands …

Quantum annealing (QA) and Quantum Alternating Operator Ansatz (QAOA) are both
heuristic quantum algorithms intended for sampling optimal solutions of combinatorial …

Quantum volume (QV) has become the de-facto standard benchmark to quantify the
capability of noisy intermediate-scale quantum (NISQ) devices. While QV values are often …

Despite the development of increasingly capable quantum computers, an experimental
demonstration of a provable algorithmic quantum speedup employing today's non-fault …

We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and
QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p= 1, 2 rounds is …

This paper proposes the use of annealing-based quantum computing for solving
combinatorial optimal power flow problems. Quantum annealers provide a physical …