Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

Simulating quantum many-body systems is a key application for emerging quantum
processors. While analog quantum simulation has already demonstrated quantum …

Suppressing errors is the central challenge for useful quantum computing, requiring
quantum error correction (QEC),,,–for large-scale processing. However, the overhead in the …

The ability to perform entangling quantum operations with low error rates in a scalable
fashion is a central element of useful quantum information processing. Neutral-atom arrays …

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

The development of scalable, high-fidelity qubits is a key challenge in quantum information
science. Neutral atom qubits have progressed rapidly in recent years, demonstrating …

Minimizing and understanding errors is critical for quantum science, both in noisy
intermediate scale quantum (NISQ) devices and for the quest towards fault-tolerant quantum …

Midcircuit operations, such as qubit state measurement or reset, are central to many tasks in
quantum information science, including quantum computing, entanglement generation, and …

Neutral-atom arrays trapped in optical potentials are a powerful platform for studying
quantum physics, combining precise single-particle control and detection with a range of …

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 …