Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …

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

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

The impressive progress in quantum hardware of the last years has raised the interest of the
quantum computing community in harvesting the computational power of such devices …

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a general-purpose
algorithm for combinatorial optimization problems whose performance can only improve with …

Realizing the potential of near-term quantum computers to solve industry-relevant
constrained-optimization problems is a promising path to quantum advantage. In this work …

Finding high-quality parameters is a central obstacle to using the quantum approximate
optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on …

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but
no quantum algorithm has yet made the leap. Noise in quantum hardware remains a …

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 …

The error rates of quantum devices are orders of magnitude higher than what is needed to
run most quantum applications. To close this gap, Quantum Error Correction (QEC) encodes …