Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …

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

The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm
for solving optimization problems on quantum computers. However, the potential of QAOA to …

Here we explore which heuristic quantum algorithms for combinatorial optimization might be
most practical to try out on a small fault-tolerant quantum computer. We compile circuits for …

We describe a simple protocol for the single-step generation of N-body entangling
interactions between trapped atomic ion qubits. We show that qubit state-dependent …

Variational quantum algorithms (VQAs) are expected to establish valuable applications on
near-term quantum computers. However, recent works have pointed out that the …

The quantum approximate optimization algorithm (QAOA) is a near-term hybrid algorithm
intended to solve combinatorial optimization problems, such as MaxCut. QAOA can be made …

In the near-term, hybrid quantum-classical algorithms hold great potential for outperforming
classical approaches. Understanding how these two computing paradigms work in tandem …

Adiabatic time evolution can be used to prepare a complicated quantum many-body state
from one that is easier to synthesize and Trotterization can be used to implement such an …

The quantum imaginary time evolution is a powerful algorithm for preparing the ground and
thermal states on near-term quantum devices. However, algorithmic errors induced by …