Gymnasium-compatible RL environments for training AI agents to synthesize quantum circuits. The framework that powers the AI transpiler passes achieving state-of-the-art results in qiskit-ibm-transpiler.
Three synthesis environments:
- Permutation Synthesis — Minimal SWAP gate implementations respecting hardware coupling
- Linear Function Synthesis — CNOT-optimal decomposition of Boolean linear functions
- Clifford Synthesis — Hardware-efficient implementations of Clifford group elements
Hardware-aware design matches real quantum device coupling maps. High-performance Rust backend enables fast training. Supports PPO, AlphaZero, and custom policies with built-in TensorBoard visualization.
The agents trained with this framework achieve near-optimal synthesis up to 65 qubits—orders of magnitude faster than SAT solvers.