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) generates an approximate
solution to combinatorial optimization problems using a variational ansatz circuit defined by …

Quantum computers may provide good solutions to combinatorial optimization problems by
leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often …

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

The design of fast algorithms for combinatorial optimization greatly contributes to a plethora
of domains such as logistics, finance, and chemistry. Quantum approximate optimization …

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 …

Quantum computing is rapidly reaching a point in which its application design and
engineering aspects must be seriously considered. However, quantum software engineering …

Quantum computing is gaining popularity across a wide range of scientific disciplines due to
its potential to solve long-standing computational problems that are considered intractable …

Many quantum algorithms seek to output a specific bitstring solving the problem of interest—
or a few if the solution is degenerate. It is the case for the quantum approximate optimization …

We show that the quantum approximate optimization algorithm (QAOA) for higher-order,
random coefficient, heavy-hex compatible spin glass Ising models has strong parameter …