🧩 QAOA: Quantum Approximate Optimization Algorithm
Explore QAOA, the quantum-classical hybrid algorithm that tackles combinatorial optimization problems like Max-Cut by alternating cost and mixer unitaries across tunable layers.
The simulation visualizes a small graph optimization problem in 3D, showing how QAOA's alternating cost and mixer layers reshape the probability of measuring each candidate solution as the circuit depth and angles change.
🔬 What It Demonstrates
The simulation visualizes a small graph optimization problem in 3D, showing how QAOA's alternating cost and mixer layers reshape the probability of measuring each candidate solution as the circuit depth and angles change.
🎮 How to Use
Pick a problem graph, drag the layer depth (p) slider to add or remove QAOA rounds, and press play to watch the classical optimizer tune the beta and gamma angles while the measurement probabilities evolve toward better cuts.
💡 Did You Know?
QAOA was proposed in 2014 by Edward Farhi, Jeffrey Goldstone, and Sam Gutmann, and as its layer count p approaches infinity, it mathematically converges to the earlier idea of adiabatic quantum computation.
Interactive 3D lab visualizing QAOA's alternating cost and mixer layers reshaping measurement probabilities toward better Max-Cut solutions on a small graph.
3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install