Benchmark

QAOA MaxCut Optimization

Quantum Approximate Optimization Algorithm (QAOA) · Optimization · 12 qubits · PennyLane, Cirq

Benchmark of the Quantum Approximate Optimization Algorithm for solving MaxCut. The original analysis (Farhi, Goldstone & Gutmann, 2014) studies regular graphs, deriving performance guarantees for 2-regular and 3-regular instances at fixed p; benchmark suites extend this to random regular and Erdos-Renyi instances. Tests the quality of approximate solutions as a function of circuit depth (p-levels) and graph size. A standard benchmark for hybrid quantum-classical optimization.

QAOAoptimizationMaxCuthybridcombinatorial

3 credible sources · last verified 6 months ago

Benchmark of the Quantum Approximate Optimization Algorithm for solving MaxCut. The original analysis (Farhi, Goldstone & Gutmann, 2014) studies regular graphs, deriving performance guarantees for 2-regular and 3-regular instances at fixed p; benchmark suites extend this to random regular and Erdos-Renyi instances. Tests the quality of approximate solutions as a function of circuit depth (p-levels) and graph size. A standard benchmark for hybrid quantum-classical optimization.

Key Metrics
Problem type
MaxCut on random graphs
Qubits tested
12
Why It Matters

The canonical benchmark for hybrid quantum-classical optimization, testing how QAOA approximation quality scales with circuit depth and graph complexity.

Hardware

Simulator / hardware-agnostic

Framework

PennyLane, Cirq