Quantum optimize
quantum_optimizeSolve a factory decision with the Quantum Approximate Optimization Algorithm. Returns the decision in plain terms, how close it is to the proven optimum, and a post-quantum signed attestation (Ed25519 + ML-DSA-87) that is anchored on chain (Base). Free.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Problem data in the shape quantum_problems describes | |
| shots | No | Measurements to sample from the trained circuit (1-100000) | |
| layers | No | QAOA depth p (1-4). Deeper finds better answers more often but runs longer. | |
| problem | Yes | balance_lines | select_lots | split_conflicts | qubo (see quantum_problems) | |
| include_qasm | No | Also return the trained circuit as OpenQASM 2.0 for real quantum hardware |