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

The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …

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

Programmable quantum systems based on Rydberg atom arrays have recently been used
for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376 …

Using a quantum processor to embed and process classical data enables the generation of
correlations between variables that are inefficient to represent through classical …

Rydberg atom arrays are among the leading contenders for the demonstration of quantum
speedups. Motivated by recent experiments with up to 289 qubits [Ebadi, Science 376, 1209 …

We propose and implement a family of quantum-informed recursive optimization (QIRO)
algorithms for combinatorial optimization problems. Our approach leverages quantum …

We propose and analyze the use of Bayesian optimization techniques to design quantum
annealing schedules with minimal user and resource requirements. We showcase our …

In this work we present a complete hybrid classical-quantum algorithm involving a quantum
sampler based on neutral-atom platforms. This approach is inspired by classical column …

Quantum computing, an emerging paradigm based on the principles of quantum mechanics,
has the potential to revolutionise various industries, including Telecommunications. This …